Triple
T15989453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave McClure |
E387785
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Dave |
E34737
|
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: Dave | Statement: [Dave McClure, givenName, Dave]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dave Context triple: [Dave McClure, givenName, Dave]
-
A.
Dave
chosen
Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
-
B.
Danny
Danny is the central character in the short story "In the Gloaming," around whom the narrative’s emotional and thematic developments revolve.
-
C.
Danny
Danny is the young, psychically gifted son of Jack Torrance in Stephen King’s horror novel "The Shining" and its film adaptations.
-
D.
Danny
Danny is the central protagonist of the film "Lowriders," a young man torn between his passion for street art and the expectations of his lowrider-obsessed family in East Los Angeles.
-
E.
Danny
Danny is a fictional character from the musical "Proud Mary."
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157829ec08190aa4a683e29a0148a |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf1cb1388190b1ebccc6705e5974 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:54 a.m.