Triple
T8412334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tammy Blanchard |
E198653
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Iceman |
E585584
|
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: The Iceman | Statement: [Tammy Blanchard, notableWork, The Iceman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Iceman Context triple: [Tammy Blanchard, notableWork, The Iceman]
-
A.
The Iceman
The Iceman is the Hall of Fame NBA shooting guard George Gervin, renowned for his smooth scoring ability and signature finger roll.
-
B.
The Iceman
The Iceman is the nickname of Dutch football legend Dennis Bergkamp, renowned for his composure, elegance, and technical brilliance on the pitch.
-
C.
The Iceman
chosen
The Iceman is a 2012 crime thriller film in which Michael Shannon portrays real-life contract killer Richard Kuklinski.
-
D.
Iceman
Iceman is the nickname of Adam Vinatieri, the legendary NFL placekicker renowned for his clutch, game-winning field goals under extreme pressure.
-
E.
Iceman
Iceman is a founding member of the X-Men with the mutant ability to generate and control ice and cold.
- 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_69ca831201b481909e137936ef99ff11 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb83e0341c819080506e696131671e |
completed | March 31, 2026, 8:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0322d1448190aceaf7486c110ff7 |
completed | April 2, 2026, 5:48 a.m. |
Created at: March 30, 2026, 6:05 p.m.