Triple
T12460833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Yawkey |
E297787
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tom |
E128299
|
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: Tom | Statement: [Tom Yawkey, givenName, Tom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Context triple: [Tom Yawkey, givenName, Tom]
-
A.
Tom
chosen
Tom is a common masculine given name, often used in English-speaking countries as a short form of Thomas.
-
B.
TOM
TOM is the ICAO airline designator used to identify TUI Airways in international aviation operations.
-
C.
TOM
TOM is the National Rail station code assigned to Tottenham Hale railway station in London, England.
-
D.
Tim
Tim is a fictional character from Robert Silverberg’s science fiction novel "The Book of Skulls," one of the four college students who seek an ancient order promising immortality at a terrible price.
-
E.
Tim
Tim is a common masculine given name used in many English-speaking countries, often as a short form of Timothy.
- 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_69d6ada270808190b1a2b2e7b02bb426 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94db465c48190bcfaf22f25ef8947 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f002b7c81909ee9d4ea3ea6d5f2 |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.