Triple
T17030699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2-26 Incident |
E413185
|
entity |
| Predicate | numberOfConspirators |
P82702
|
FINISHED |
| Object | approximately 1,400 soldiers |
—
|
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: approximately 1,400 soldiers | Statement: [2-26 Incident, numberOfConspirators, approximately 1,400 soldiers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfConspirators Context triple: [2-26 Incident, numberOfConspirators, approximately 1,400 soldiers]
-
A.
hasApproximateNumberOfConspirators
chosen
Indicates that an entity is associated with an estimated or approximate count of conspirators involved with it.
-
B.
conspirator
Indicates that an entity participates with others in planning or carrying out a secret or illicit scheme or action.
-
C.
numberOfMainImpostors
Indicates the count of primary or main impostor entities involved in a given context or scenario.
-
D.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
E.
numberOfConsuls
Indicates the number of consuls associated with or holding office in relation to 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d5d918ec8190b54c40c2a5e9b6b9 |
completed | April 18, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69e35d5be7f48190af9db67a1e23850f |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:33 a.m.