Triple
T4945243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Anderson |
E111033
|
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 Anderson, givenName, Tom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Context triple: [Tom Anderson, 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.
Tim
Tim is the given name of Tim Wu, a prominent legal scholar and policy advocate known for coining the term "net neutrality."
-
D.
Tony
Tony is one of the central protagonists in Margaret Atwood’s novel "The Robber Bride," known for her intellectual, introspective nature and complex relationships with the other main characters.
-
E.
Tony
Tony is a central, shape-shifting conman character in the fantasy film "The Imaginarium of Doctor Parnassus," notably portrayed by multiple actors including Heath Ledger, Johnny Depp, Jude Law, and Colin Farrell.
- 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_69bd441721cc819085c7e33fe0876818 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd70a8e5388190882831d7828441d3 |
completed | March 20, 2026, 4:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77c6566c8190b0c76c05b9d82053 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:31 p.m.