Triple
T2085114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benghazi attack congressional hearings |
E45330
|
entity |
| Predicate | numberOfInvestigations |
P35717
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Benghazi attack congressional hearings, numberOfInvestigations, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInvestigations Context triple: [Benghazi attack congressional hearings, numberOfInvestigations, multiple]
-
A.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
B.
typeOfInvestigation
Indicates the specific kind or category of investigation being conducted or referred to in the relationship.
-
C.
investigatedBy
Indicates that an entity is the subject of an investigation carried out by another entity.
-
D.
hasNumberOfCasesApprox
Indicates that an entity is associated with an approximate (not exact) count of cases.
-
E.
usesInvestigativeMethods
Indicates that an entity employs investigative techniques or procedures to gather information, analyze evidence, or uncover facts.
- 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba53d4488190a7d9eabcb6904e8e |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b298a48190b4bdf7c9800b058d |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb94ec400819097596732aabed854 |
completed | March 7, 2026, 5:36 a.m. |
Created at: March 4, 2026, 7:41 p.m.