Triple
T5838995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Snow |
E129544
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Peter Snow |
E551846
|
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: Peter Snow | Statement: [Dan Snow, relative, Peter Snow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Snow Context triple: [Dan Snow, relative, Peter Snow]
-
A.
Peter Snow
chosen
Peter Snow is a British television and radio presenter and historian, best known for his long-running work as an election night analyst for the BBC.
-
B.
Peter Rinearson
Peter Rinearson is an American journalist and author best known for co-authoring Bill Gates’s book "The Road Ahead" and for his Pulitzer Prize–winning feature writing.
-
C.
Christopher Noxon
Christopher Noxon is an American journalist and author known for his nonfiction work and for being married to television producer Jenji Kohan.
-
D.
Ben Hanscom
Ben Hanscom is one of the central members of the Losers' Club in Stephen King's horror novel "It," known for his intelligence, kindness, and pivotal role in confronting the creature terrorizing Derry.
-
E.
Andrew Hill Newman
Andrew Hill Newman is an American actor best known for his supporting roles in television comedies and dramas.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c034a852f88190a5d2c4b24ee17491 |
completed | March 22, 2026, 6:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b0f371008190b11cd4da8a55dbb9 |
completed | March 23, 2026, 3:18 a.m. |
Created at: March 22, 2026, 3:54 p.m.