Triple
T6778383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1994 National League Championship Series |
E155615
|
entity |
| Predicate | hadNoVenue |
P72749
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [1994 National League Championship Series, hadNoVenue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadNoVenue Context triple: [1994 National League Championship Series, hadNoVenue, true]
-
A.
hadNo
Indicates that one entity completely lacked or did not possess another entity, attribute, or relationship.
-
B.
hasVenueContext
Indicates that an entity is associated with a particular venue or setting that provides contextual information about where it occurs or is situated.
-
C.
hasVenueFunction
Indicates that a venue serves a particular function or role (such as hosting events, performances, or specific activities).
-
D.
hasHostedVenue
Indicates that a particular venue has served as the location for hosting a specific event or activity.
-
E.
usualVenueSince
Indicates that a particular venue has been the regular or customary location for something (e.g., an event or activity) starting from a specified point in time.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2689d408190bc2c1ce4ae9c1b13 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d182213c819086fcbbfd3d64d80b |
completed | March 27, 2026, 6:50 p.m. |
Created at: March 27, 2026, 2:14 p.m.