Triple
T19789423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trapped Ashes |
E475368
|
entity |
| Predicate | hasCastMember |
P2308
|
FINISHED |
| Object |
Rachel Veltri
Rachel Veltri is an American actress best known for her role in the horror anthology film "Trapped Ashes."
|
E1399648
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rachel Veltri | Statement: [Trapped Ashes, hasCastMember, Rachel Veltri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachel Veltri Context triple: [Trapped Ashes, hasCastMember, Rachel Veltri]
-
A.
Carla DiBello
Carla DiBello is an American producer and businesswoman known for her work in reality television and her close association with the Kardashian–Jenner family.
-
B.
Lisa Vultaggio
Lisa Vultaggio is a Canadian actress best known for her role as Hannah Scott on the soap opera "General Hospital."
-
C.
Alexandra Papenfus
Alexandra Papenfus is a person after whom another individual named Alexandra was named, suggesting she holds personal or familial significance to the namer.
-
D.
Laura Terruso
Laura Terruso is an American filmmaker and screenwriter known for her work on character-driven comedies and collaborations with director Michael Showalter.
-
E.
Heidi Tagliavini
Heidi Tagliavini is a Swiss diplomat known for her high-profile roles in international conflict mediation and peace negotiations, particularly in the post-Soviet space.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rachel Veltri Triple: [Trapped Ashes, hasCastMember, Rachel Veltri]
Generated description
Rachel Veltri is an American actress best known for her role in the horror anthology film "Trapped Ashes."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rachel Veltri Target entity description: Rachel Veltri is an American actress best known for her role in the horror anthology film "Trapped Ashes."
-
A.
Carla DiBello
Carla DiBello is an American producer and businesswoman known for her work in reality television and her close association with the Kardashian–Jenner family.
-
B.
Lisa Vultaggio
Lisa Vultaggio is a Canadian actress best known for her role as Hannah Scott on the soap opera "General Hospital."
-
C.
Alexandra Papenfus
Alexandra Papenfus is a person after whom another individual named Alexandra was named, suggesting she holds personal or familial significance to the namer.
-
D.
Laura Terruso
Laura Terruso is an American filmmaker and screenwriter known for her work on character-driven comedies and collaborations with director Michael Showalter.
-
E.
Heidi Tagliavini
Heidi Tagliavini is a Swiss diplomat known for her high-profile roles in international conflict mediation and peace negotiations, particularly in the post-Soviet space.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e51b014081908b263e167370529a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6538ae5108190b80eb7de6f445f02 |
completed | April 20, 2026, 4:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dbb3464c8190bdcfdc4b31ab71b6 |
completed | May 16, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a07dc7421b48190a81724e702727d05 |
completed | May 16, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07dcf2d88c8190bbf9aa42f9fe8c6d |
completed | May 16, 2026, 2:56 a.m. |
Created at: April 10, 2026, 1:49 p.m.