Triple
T16317376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Bundy |
E396205
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bundy |
E563582
|
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: Bundy | Statement: [Al Bundy, familyName, Bundy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bundy Context triple: [Al Bundy, familyName, Bundy]
-
A.
Bundy
chosen
Bundy is a surname most notably associated with McGeorge Bundy, the influential U.S. National Security Advisor during the Kennedy and Johnson administrations.
-
B.
Bonger
Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
-
C.
Bubley
Bubley is the surname of Esther Bubley, an influential American photographer known for her documentary work in the mid-20th century.
-
D.
Bonderman
Bonderman is a surname most prominently associated with American billionaire investor and private equity pioneer David Bonderman.
-
E.
Bonnett
Bonnett is a surname most notably associated with American NASCAR driver Neil Bonnett.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e296b31b988190bb1fde36dae11bbd |
completed | April 17, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002606f0e0819081f50dae9e6b7a0d |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:06 a.m.