Triple
T4005370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayelet Zurer |
E89512
|
entity |
| Predicate | playedCharacter |
P1507
|
FINISHED |
| Object |
Lara Lor-Van
Lara Lor-Van is a Kryptonian scientist and the biological mother of Superman (Kal-El) in the DC Comics universe.
|
E407479
|
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: Lara Lor-Van | Statement: [Ayelet Zurer, playedCharacter, Lara Lor-Van]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lara Lor-Van Context triple: [Ayelet Zurer, playedCharacter, Lara Lor-Van]
-
A.
Fennec Shand
Fennec Shand is a skilled mercenary and elite assassin in the Star Wars universe who becomes a close ally and enforcer to Boba Fett.
-
B.
Rose Tico
Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
-
C.
Marella Ciano
Marella Ciano was an Italian aristocrat and socialite, best known as the daughter of Edda Mussolini and granddaughter of dictator Benito Mussolini.
-
D.
Cara Dune
Cara Dune is a former Rebel shock trooper turned mercenary who becomes a key ally to the titular bounty hunter in the Star Wars series "The Mandalorian."
-
E.
Emma Bardac
Emma Bardac was a French singer and socialite best known as the second wife and muse of composer Claude Debussy.
- 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: Lara Lor-Van Triple: [Ayelet Zurer, playedCharacter, Lara Lor-Van]
Generated description
Lara Lor-Van is a Kryptonian scientist and the biological mother of Superman (Kal-El) in the DC Comics universe.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lara Lor-Van Target entity description: Lara Lor-Van is a Kryptonian scientist and the biological mother of Superman (Kal-El) in the DC Comics universe.
-
A.
Fennec Shand
Fennec Shand is a skilled mercenary and elite assassin in the Star Wars universe who becomes a close ally and enforcer to Boba Fett.
-
B.
Rose Tico
Rose Tico is a Resistance mechanic-turned-hero in the Star Wars sequel trilogy who fights alongside Finn against the First Order.
-
C.
Marella Ciano
Marella Ciano was an Italian aristocrat and socialite, best known as the daughter of Edda Mussolini and granddaughter of dictator Benito Mussolini.
-
D.
Cara Dune
Cara Dune is a former Rebel shock trooper turned mercenary who becomes a key ally to the titular bounty hunter in the Star Wars series "The Mandalorian."
-
E.
Emma Bardac
Emma Bardac was a French singer and socialite best known as the second wife and muse of composer Claude Debussy.
- 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa5f7b308190adaad864eec98936 |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c648d3c8190a85e5cdfb20f6044 |
completed | March 14, 2026, 11:54 a.m. |
| NEDg | Description generation | batch_69b54cf3da208190aa844c9ea66354fe |
completed | March 14, 2026, 11:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b55159dc288190a63d5f5164b73bbb |
completed | March 14, 2026, 12:15 p.m. |
Created at: March 9, 2026, 3:34 p.m.