Triple
T14460762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunnm |
E358576
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Gally |
E863495
|
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: Gally | Statement: [Gunnm, mainCharacter, Gally]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gally Context triple: [Gunnm, mainCharacter, Gally]
-
A.
Gally
Gally is the nickname of Galahad Threepwood, a roguish and charming member of the eccentric Blandings Castle family in P. G. Wodehouse’s comic novels.
-
B.
Gally
chosen
Gally is a prominent character in James Dashner’s dystopian Maze Runner series, known for his antagonistic yet complex relationship with the protagonist and the Glade’s social order.
-
C.
Nagg
Nagg is a legless, elderly character in Samuel Beckett’s play "Endgame," known for living in a trash bin and engaging in bleakly comic exchanges with his wife Nell.
-
D.
Gurgi
Gurgi is a timid yet loyal, creature-like companion character from Disney’s animated fantasy film "The Black Cauldron."
-
E.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91abc1008190a19de4f8f0112c9d |
completed | April 14, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6495660081908ab9db11939e74f7 |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:19 a.m.