Triple
T11834611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pen 4 |
E281482
|
entity |
| Predicate | crowdManagementIssue |
P101745
|
FINISHED |
| Object | lack of effective monitoring of crowd density on 15 April 1989 |
—
|
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: lack of effective monitoring of crowd density on 15 April 1989 | Statement: [Pen 4, crowdManagementIssue, lack of effective monitoring of crowd density on 15 April 1989]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crowdManagementIssue Context triple: [Pen 4, crowdManagementIssue, lack of effective monitoring of crowd density on 15 April 1989]
-
A.
crowdAction
Indicates an action or behavior performed collectively by a group of individuals acting as a crowd.
-
B.
hasEventDayCrowdManagement
Indicates that specific crowd management measures or responsibilities are associated with the day on which an event takes place.
-
C.
crowdWas
Indicates that a crowd possessed or exhibited a particular state, quality, or condition.
-
D.
hasCrowdLevel
Indicates the degree or intensity of how crowded a place, event, or situation is.
-
E.
numberOfProtesters
Indicates the total count of individuals participating as protesters in a given event or context.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62e7e408190998bebe346c82e89 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
| PDg | Predicate description generation | batch_69d8a43cc0c881909fed7cd759fe90b1 |
completed | April 10, 2026, 7:18 a.m. |
Created at: April 8, 2026, 9:43 p.m.