Triple
T5523303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cedar Revolution |
E144863
|
entity |
| Predicate | estimatedParticipants |
P1131
|
FINISHED |
| Object | over one million people in March 14 demonstration |
—
|
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: over one million people in March 14 demonstration | Statement: [Cedar Revolution, estimatedParticipants, over one million people in March 14 demonstration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedParticipants Context triple: [Cedar Revolution, estimatedParticipants, over one million people in March 14 demonstration]
-
A.
numberOfParticipants
chosen
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
B.
vowOfParticipants
Indicates that certain participants formally promise or commit themselves to a specified action, condition, or relationship.
-
C.
hasParticipants
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
D.
eventParticipant
Indicates that an entity takes part in, is involved in, or participates in a particular event.
-
E.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
- 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_69c008f873a481909b4d9f7e2db3c37d |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f85c8508190a0a089402b49a04f |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0a06348190b39ac9fe80d2836a |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:34 p.m.