Triple

T23788395
Position Surface form Disambiguated ID Type / Status
Subject Caroline, or Change E588020 entity
Predicate notableCharacter P1481 FINISHED
Object Emmie Thibodeaux
Emmie Thibodeaux is a politically aware and outspoken teenage daughter in the musical "Caroline, or Change," representing the emerging civil rights consciousness of the 1960s.
E1602908 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: Emmie Thibodeaux | Statement: [Caroline, or Change, notableCharacter, Emmie Thibodeaux]
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: Emmie Thibodeaux
Triple: [Caroline, or Change, notableCharacter, Emmie Thibodeaux]
Generated description
Emmie Thibodeaux is a politically aware and outspoken teenage daughter in the musical "Caroline, or Change," representing the emerging civil rights consciousness of the 1960s.

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_69e2490f4ad48190b690878eec3596c6 completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1c633f7908190bac7fdac5990920a completed April 29, 2026, 8:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f760a06f88190a59004a142cd954b completed May 21, 2026, 9:15 p.m.
NEDg Description generation batch_6a0f77b76ab08190b2caf42777492249 completed May 21, 2026, 9:23 p.m.
NED2 Entity disambiguation (via description) batch_6a0f788c4c108190b79e1ea898be2a80 completed May 21, 2026, 9:26 p.m.
Created at: April 17, 2026, 7:17 p.m.