Triple
T12791396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Celebrity |
E305772
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | The Celebrity |
E305772
|
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: The Celebrity | Statement: [The Celebrity, hasTitle, The Celebrity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Celebrity Context triple: [The Celebrity, hasTitle, The Celebrity]
-
A.
The Celebrity
chosen
The Celebrity is a novel by Laura Z. Hobson, best known for its incisive exploration of fame, identity, and personal integrity.
-
B.
Fuente de la Fama
Fuente de la Fama is a celebrated Baroque fountain in San Ildefonso, Spain, renowned for its elaborate sculptural design and association with the royal gardens of La Granja.
-
C.
Koho
Koho is an Austroasiatic language spoken by the Koho ethnic group in Vietnam’s Central Highlands.
-
D.
Dame
Dame is the popular nickname of NBA All-Star point guard Damian Lillard, known for his clutch shooting and leadership.
-
E.
Dame
Dame is a British honorific title bestowed primarily upon women in recognition of significant contributions to national life, often in the arts, public service, or other distinguished fields.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e6b55248190ab938e69eb263612 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68508e4488190bb57a1ade93987ab |
completed | May 2, 2026, 11:13 p.m. |
Created at: April 9, 2026, 5:30 p.m.