Triple
T10073060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Milton Babbitt |
E213676
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Babbitt |
E168724
|
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: Babbitt | Statement: [Milton Babbitt, familyName, Babbitt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Babbitt Context triple: [Milton Babbitt, familyName, Babbitt]
-
A.
Babbitt
chosen
Babbitt is a surname most notably associated with American literary critic and academic Irving Babbitt.
-
B.
Babbitt
Babbitt is a 1934 American film adaptation of Sinclair Lewis’s novel, featuring Guy Kibbee in the title role as a middle-class businessman confronting the emptiness of his conformist life.
-
C.
Solidere
Solidere is a Lebanese real estate company responsible for the post-civil war reconstruction and development of Beirut’s central district.
-
D.
Bondo
Bondo is a town in western Kenya’s Nyanza region, known as an administrative and commercial center near Lake Victoria.
-
E.
Nickel
Nickel is a chemical element and transition metal known for its hardness, corrosion resistance, and widespread use in alloys and batteries.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd013c9d0819091ebe6fc399832de |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d29ab376488190bfb3efdb3f240cca |
completed | April 5, 2026, 5:24 p.m. |
Created at: March 30, 2026, 8:59 p.m.