Triple
T20586900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonel Hathi’s March |
E505810
|
entity |
| Predicate | usesCharacter |
P35699
|
FINISHED |
| Object | Colonel Hathi |
—
|
NE NERFINISHED |
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: Colonel Hathi | Statement: [Colonel Hathi’s March, usesCharacter, Colonel Hathi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colonel Hathi Context triple: [Colonel Hathi’s March, usesCharacter, Colonel Hathi]
-
A.
Colonel Hathi
chosen
Colonel Hathi is a pompous but well-meaning elephant military leader from Disney’s animated film "The Jungle Book."
-
B.
Colonel Rol
Colonel Rol was the nom de guerre of French Resistance leader Henri Rol-Tanguy, who played a key role in the liberation of Paris during World War II.
-
C.
Colonel Haki
Colonel Haki is a shrewd and persistent Turkish police officer who aids in unraveling the criminal mystery at the heart of Eric Ambler’s novel "The Mask of Dimitrios."
-
D.
Colonel Bob
Colonel Bob is a prominent peak in Washington State’s Olympic Peninsula, known for its rugged wilderness setting and panoramic views.
-
E.
Colonel Howard
Colonel Howard is a fictional military officer character featured in the film "The Pilot."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4b9669c8190b8e81fc72817d42c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a977fb18819085fee5cf5d45c1b0 |
completed | April 20, 2026, 10:32 p.m. |
Created at: April 16, 2026, 11:40 a.m.