Triple
T8267666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Harmon |
E193341
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Harmon |
E449258
|
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: Harmon | Statement: [Mark Harmon, familyName, Harmon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harmon Context triple: [Mark Harmon, familyName, Harmon]
-
A.
Harmon
chosen
Harmon is the maiden surname of Ellen G. White, a co-founder and prophetic figure of the Seventh-day Adventist Church.
-
B.
Haro
Haro is a historic town in Spain’s La Rioja region, renowned for its wineries and annual wine festival.
-
C.
Haroldson
Haroldson is the distinctive given name of American oil tycoon and political activist H. L. Hunt.
-
D.
Harbison
Harbison is a surname most notably associated with American composer John Harbison, known for his contributions to contemporary classical music.
-
E.
Hibler
Hibler is a surname most notably associated with Winston Hibler, an American screenwriter, producer, and narrator known for his work on Walt Disney nature documentaries and animated films.
- 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_69ca82e081d48190986beaa51f498ab9 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb794fc4208190b268bc69ff2b28a9 |
completed | March 31, 2026, 7:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd6833065c8190945e88022ad2869d |
completed | April 1, 2026, 6:47 p.m. |
Created at: March 30, 2026, 5:50 p.m.