Triple
T14876693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Heck |
E349885
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Heck |
E1086300
|
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: Heck | Statement: [Don Heck, familyName, Heck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heck Context triple: [Don Heck, familyName, Heck]
-
A.
Heck
chosen
Heck is a surname most notably associated with Richard F. Heck, the Nobel Prize–winning chemist known for the Heck reaction in organic chemistry.
-
B.
Hick
Hick is a 2011 coming-of-age drama film about a young Nebraska girl who hitchhikes to Las Vegas and encounters a series of dangerous and transformative experiences.
-
C.
Yank
Yank is a central character in John Patrick's wartime drama "The Hasty Heart," portrayed as a tough, emotionally guarded American soldier whose interactions with fellow patients reveal his vulnerability and capacity for friendship.
-
D.
Heckerling
Heckerling is the surname of American film director and screenwriter Amy Heckerling, known for works like "Fast Times at Ridgemont High" and "Clueless."
-
E.
Heckman
Heckman is a surname most prominently associated with Nobel Prize–winning economist James J. Heckman, known for his work on econometrics and labor economics.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e4e4448190a8796573bc6d1069 |
completed | April 15, 2026, 12:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b54ad7c819082575245da07e358 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:55 a.m.