Triple
T13278808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N106US |
E316262
|
entity |
| Predicate | totalOccupantsDuringEvent |
P79202
|
FINISHED |
| Object | 155 |
—
|
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: 155 | Statement: [N106US, totalOccupantsDuringEvent, 155]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalOccupantsDuringEvent Context triple: [N106US, totalOccupantsDuringEvent, 155]
-
A.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
B.
guestCountApproximate
Indicates that the number of guests involved is represented as an estimated or approximate count rather than an exact figure.
-
C.
capacityDuringEvent
chosen
Indicates the maximum number of occupants or usage level that a place, system, or resource can handle specifically during a given event.
-
D.
numberOfMembersSeated
Indicates the count of members who are currently seated in a given context or setting.
-
E.
numberOfEvents
Indicates the quantity or count of events associated with a given entity or context.
- F. None of above.
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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:26 p.m.