Triple
T1988262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mataf area |
E43189
|
entity |
| Predicate | hasTimeRestriction |
P33304
|
FINISHED |
| Object | crowd management periods |
—
|
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: crowd management periods | Statement: [Mataf area, hasTimeRestriction, crowd management periods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimeRestriction Context triple: [Mataf area, hasTimeRestriction, crowd management periods]
-
A.
hasLimitation
Indicates that an entity is subject to a constraint, restriction, or boundary that limits its scope, capability, or applicability.
-
B.
hasSemanticRestriction
Indicates that a concept or relation is constrained in meaning or usage by specific semantic conditions or limitations.
-
C.
hasValidityPeriod
chosen
Indicates that something is associated with a specific time span during which it is considered valid or in effect.
-
D.
demographicRestriction
Indicates that participation, access, or applicability is limited or conditioned based on specific demographic characteristics (such as age, gender, ethnicity, or similar attributes).
-
E.
hasTimeStart
Indicates that an event, process, or state begins at a specific point in time.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.