Triple
T6627772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilmore Girls |
E149846
|
entity |
| Predicate | supportingActor |
P7748
|
FINISHED |
| Object |
Liza Weil
Liza Weil is an American actress best known for her roles as Paris Geller on "Gilmore Girls" and Bonnie Winterbottom on "How to Get Away with Murder."
|
E633969
|
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: Liza Weil | Statement: [Gilmore Girls, supportingActor, Liza Weil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liza Weil Context triple: [Gilmore Girls, supportingActor, Liza Weil]
-
A.
Liza Snyder
Liza Snyder is an American television actress best known for her comedic roles on sitcoms such as "Yes, Dear" and "Man with a Plan."
-
B.
Liz Gorinsky
Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
-
C.
Shari Weiser
Shari Weiser is a puppeteer and performer best known for physically portraying the character Hoggle in Jim Henson’s fantasy film "Labyrinth."
-
D.
Rachel Leibowitz
Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
-
E.
Liza Huber
Liza Huber is an American actress best known for her role on the soap opera "Passions" and as the daughter of daytime television star Susan Lucci.
- 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: Liza Weil Triple: [Gilmore Girls, supportingActor, Liza Weil]
Generated description
Liza Weil is an American actress best known for her roles as Paris Geller on "Gilmore Girls" and Bonnie Winterbottom on "How to Get Away with Murder."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Liza Weil Target entity description: Liza Weil is an American actress best known for her roles as Paris Geller on "Gilmore Girls" and Bonnie Winterbottom on "How to Get Away with Murder."
-
A.
Liza Snyder
Liza Snyder is an American television actress best known for her comedic roles on sitcoms such as "Yes, Dear" and "Man with a Plan."
-
B.
Liz Gorinsky
Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
-
C.
Shari Weiser
Shari Weiser is a puppeteer and performer best known for physically portraying the character Hoggle in Jim Henson’s fantasy film "Labyrinth."
-
D.
Rachel Leibowitz
Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
-
E.
Liza Huber
Liza Huber is an American actress best known for her role on the soap opera "Passions" and as the daughter of daytime television star Susan Lucci.
- 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_69c687ee50048190aa151765bef16193 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6afa2e4a48190ba3c70013bab14f2 |
completed | March 27, 2026, 4:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7616ff6fc8190b4e9e7810be9064b |
completed | March 28, 2026, 5:04 a.m. |
| NEDg | Description generation | batch_69c764224d1c81909a0a631e284eb9d6 |
completed | March 28, 2026, 5:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76485b7748190b873b3701178201d |
completed | March 28, 2026, 5:17 a.m. |
Created at: March 27, 2026, 1:59 p.m.