Triple
T37835528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bigby Wolf |
E943326
|
entity |
| Predicate | firstAppearanceInVideoGames |
P137991
|
FINISHED |
| Object | The Wolf Among Us |
E278228
|
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 Wolf Among Us | Statement: [Bigby Wolf, firstAppearanceInVideoGames, The Wolf Among Us]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAppearanceInVideoGames Context triple: [Bigby Wolf, firstAppearanceInVideoGames, The Wolf Among Us]
-
A.
firstAppearanceGames
chosen
Indicates the games in which an entity (such as a character, item, or concept) made its first appearance.
-
B.
appearedInVideoGame
Indicates that an entity is featured as a character, element, or content within a specific video game.
-
C.
firstAppearanceFranchise
Indicates the franchise in which an entity made its first appearance.
-
D.
firstAppearanceApprox
Indicates that one entity is the approximate or estimated first appearance of another entity in time or context.
-
E.
firstAppearanceTV
Indicates the television show or episode in which an entity is depicted or mentioned for the first time.
- F. None of above.
Provenance (4 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_69f76eeb0f7081908d6d3adbc469889c |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a4193af1d2c8190b8541a7074bee1a6 |
completed | June 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_6a037a1772e48190ba738c6d11b321e2 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:19 p.m.