Triple

T32113520
Position Surface form Disambiguated ID Type / Status
Subject Took E820177 entity
Predicate notableMember P10 FINISHED
Object Esmeralda Took
Esmeralda Took is a hobbit of the Took family in J.R.R. Tolkien’s Middle-earth legendarium, known primarily as the mother of Merry Brandybuck.
E1994681 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: Esmeralda Took | Statement: [Took, notableMember, Esmeralda Took]
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: Esmeralda Took
Triple: [Took, notableMember, Esmeralda Took]
Generated description
Esmeralda Took is a hobbit of the Took family in J.R.R. Tolkien’s Middle-earth legendarium, known primarily as the mother of Merry Brandybuck.

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_69f3490209c881908ec0241476715f15 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b906a92c819096335394dd7f767e completed May 3, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3056ea20008190b4b1b0cd7948b4bd completed June 15, 2026, 7:47 p.m.
NEDg Description generation batch_6a31af0dd4b48190be2aa9c952a9aff6 completed June 16, 2026, 8:16 p.m.
NED2 Entity disambiguation (via description) batch_6a31bab61f508190a4bfde1478397f6c completed June 16, 2026, 9:05 p.m.
Created at: May 1, 2026, 12:27 a.m.