Triple
T14739344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin McKinney |
E346299
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Esthero |
E198997
|
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: Esthero | Statement: [Martin McKinney, collaboratedWith, Esthero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esthero Context triple: [Martin McKinney, collaboratedWith, Esthero]
-
A.
Esthero
chosen
Esthero is a Canadian singer-songwriter known for her eclectic blend of trip hop, jazz, and alternative pop.
-
B.
Luciana
Luciana is a feminine given name of Latin origin, commonly used in Spanish- and Portuguese-speaking countries.
-
C.
Licia
Licia is a shortened or diminutive form of the given name Felicia.
-
D.
Cleo
Cleo is the indigenous live-in housekeeper and emotional center of Alfonso Cuarón’s film "Roma," whose personal struggles unfold against the backdrop of 1970s Mexico City.
-
E.
Cleo
Cleo is one of the four central bank-robbing friends in the 1996 crime film "Set It Off," known for her tough, fearless demeanor and loyalty to her crew.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7345680819093e901233a064e48 |
completed | April 14, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0ce6514c8190a37b023dcc0c1b1a |
completed | May 8, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:29 a.m.