Triple
T3121683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Moore |
E65198
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Moore |
E32614
|
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: Moore | Statement: [Michael Moore, familyName, Moore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moore Context triple: [Michael Moore, familyName, Moore]
-
A.
Moore
Moore is the middle name of Edward M. Kennedy, the long-serving U.S. senator from Massachusetts and prominent member of the Kennedy political family.
-
B.
Moore
chosen
Moore is a common English-language surname borne by numerous notable individuals across fields such as science, politics, entertainment, and sports.
-
C.
Moorehead
Moorehead is the surname of American actress Agnes Moorehead, renowned for her work in film, radio, and television, including her iconic role as Endora on the TV series "Bewitched."
-
D.
Mott
Mott is a surname most notably associated with Sir Nevill Mott, the Nobel Prize–winning British physicist recognized for his work on the electronic structure of magnetic and disordered systems.
-
E.
Briggs
Briggs is a surname most prominently associated with Lance Briggs, a former NFL linebacker best known for his career with the Chicago Bears.
- 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_69ad8580c72481909672d37acf647893 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada52ab05c819088204bbb608c837c |
completed | March 8, 2026, 4:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f6f57fc8190a5f50028792ac394 |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.