Triple
T4390524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marielle Heller |
E99349
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Heller
Heller is a surname shared by various notable individuals across fields such as film, literature, science, and politics.
|
E435198
|
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: Heller | Statement: [Marielle Heller, familyName, Heller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heller Context triple: [Marielle Heller, familyName, Heller]
-
A.
Heller
The Heller is a river in Germany that serves as a right-bank tributary of the Sieg.
-
B.
The Hill
The Hill is a famous public vantage point overlooking Epsom Downs Racecourse, known for offering free, expansive views of major horse racing events like The Derby.
-
C.
Die Hart
Die Hart is an action-comedy series starring Kevin Hart as a fictionalized version of himself trying to become an action movie star, blending Hollywood satire with over-the-top stunts.
-
D.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
-
E.
Barron
Barron is a surname of English origin borne by various notable individuals across fields such as law, politics, and the arts.
- 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: Heller Triple: [Marielle Heller, familyName, Heller]
Generated description
Heller is a surname shared by various notable individuals across fields such as film, literature, science, and politics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Heller Target entity description: Heller is a surname shared by various notable individuals across fields such as film, literature, science, and politics.
-
A.
Heller
The Heller is a river in Germany that serves as a right-bank tributary of the Sieg.
-
B.
The Hill
The Hill is a famous public vantage point overlooking Epsom Downs Racecourse, known for offering free, expansive views of major horse racing events like The Derby.
-
C.
Die Hart
Die Hart is an action-comedy series starring Kevin Hart as a fictionalized version of himself trying to become an action movie star, blending Hollywood satire with over-the-top stunts.
-
D.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
-
E.
Barron
Barron is a surname of English origin borne by various notable individuals across fields such as law, politics, and the arts.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352843d7c8190929b94c94eaa63df |
completed | March 12, 2026, 11:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e530428881908d125971263bd747 |
completed | March 14, 2026, 10:46 p.m. |
| NEDg | Description generation | batch_69b5e629115881908436a81b5774ac24 |
completed | March 14, 2026, 10:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5e68c960c8190a946574120a50047 |
completed | March 14, 2026, 10:51 p.m. |
Created at: March 12, 2026, 11:19 p.m.