Triple
T2436904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hardy |
E52981
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Hardy |
E120385
|
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: Hardy | Statement: [Tom Hardy, familyName, Hardy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hardy Context triple: [Tom Hardy, familyName, Hardy]
-
A.
Hardy
chosen
Hardy is a surname most famously associated with the English mathematician G. H. Hardy, known for his contributions to number theory and mathematical analysis.
-
B.
Ted Hardie
Ted Hardie is an Internet engineering expert and long-time IETF leader known for his work on real-time communications and web technologies.
-
C.
Aldous
Aldous is a masculine given name most famously borne by the English writer and philosopher Aldous Huxley.
-
D.
Oldfield Thomas
Oldfield Thomas was a prominent British zoologist and taxonomist known for his extensive work in describing and classifying mammals, particularly marsupials and rodents.
-
E.
Arthur Housman
Arthur Housman was an American character actor of the silent and early sound film era, best remembered for his frequent portrayals of comic drunkards in numerous Hollywood movies.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f342e88190a430b02842ded418 |
completed | March 7, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aebf7085b88190938c4eefa4380970 |
completed | March 9, 2026, 12:39 p.m. |
Created at: March 6, 2026, 9:43 p.m.