Triple
T37662164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicken Jockey |
E937739
|
entity |
| Predicate | threatLevelEarlyGame |
P189774
|
FINISHED |
| Object | high |
—
|
LITERAL 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: high | Statement: [Chicken Jockey, threatLevelEarlyGame, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threatLevelEarlyGame Context triple: [Chicken Jockey, threatLevelEarlyGame, high]
-
A.
threatLevelDescription
Indicates a textual description that characterizes the severity or nature of a threat level associated with an entity or situation.
-
B.
threatLevelInNarrative
Indicates the degree of danger or risk that a subject poses or experiences within the context of a narrative or storyline.
-
C.
threatTypeEngaged
Indicates that an entity has actively engaged with or responded to a specific type of threat.
-
D.
threatCategory
Indicates the classification of a threat according to its type, severity, or nature within a defined risk or security framework.
-
E.
threatEncounteredNear
Indicates that a threat was encountered in close spatial proximity to a specified reference point or entity.
- F. None of above. chosen
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_69f76ed6df7c8190b018e5baea716ceb |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbca6c066c8190a1599202f341417f |
completed | May 6, 2026, 11:10 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fbc9d0854c8190aa00093274afebb8 |
completed | May 6, 2026, 11:08 p.m. |
Created at: May 3, 2026, 4:18 p.m.