Triple
T15595903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantasy |
E374889
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | “Haywood” |
E343236
|
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: “Haywood” | Statement: [Fantasy, hasPart, “Haywood”]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: “Haywood” Context triple: [Fantasy, hasPart, “Haywood”]
-
A.
Haywood
chosen
Haywood is the given name of Haywood S. Hansell, a U.S. Air Force general known for his role in developing strategic bombing doctrine during World War II.
-
B.
Hayne
Hayne is a surname most notably associated with Robert Y. Hayne, a prominent 19th-century American politician and orator from South Carolina.
-
C.
Hayes
Hayes is a common English surname borne by numerous notable figures in politics, entertainment, sports, and other fields.
-
D.
Hayes
Hayes is a town in the southern Jamaican parish of Clarendon, known historically for its sugar estates and bauxite-related industry.
-
E.
Hayes
Hayes is a suburban district in southeast London, England, known for its residential character and green spaces within the London Borough of Bromley.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5f9db8819083abf80f01f32b3d |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56ca72ec8190a237db843dc6d625 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:12 a.m.