Triple
T9979247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christine Collins |
E196407
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Christine Collins |
E196407
|
NE FINISHED |
How this triple was built (2 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: Christine Collins | Statement: [Christine Collins, name, Christine Collins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christine Collins Context triple: [Christine Collins, name, Christine Collins]
-
A.
Christine Collins
chosen
Christine Collins was a real-life Los Angeles mother whose 1928 fight against police corruption and search for her missing son became the basis for the film "Changeling."
-
B.
Coleen Rowley
Coleen Rowley is a former FBI special agent and whistleblower known for exposing intelligence failures prior to the September 11 attacks.
-
C.
Cynthia Murphy
Cynthia Murphy is a central maternal character in the musical "Dear Evan Hansen," known as the caring but emotionally strained mother of Connor and Zoe Murphy.
-
D.
Elaine Ryan
Elaine Ryan was a screenwriter best known for her work on classic Hollywood films such as "Babes on Broadway."
-
E.
Christine Weiss
Christine Weiss is known as the wife of French politician Gérard Larcher, longtime President of the French Senate.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82efbce081908179b4b9c65096eb |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb850bde48190a06b77757f8c081b |
completed | April 2, 2026, 12:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257d3fc308190b82b3731139d15cb |
completed | April 5, 2026, 12:38 p.m. |
Created at: March 30, 2026, 8:49 p.m.