Triple
T14968983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Representatives (Libya) |
E373265
|
entity |
| Predicate | seatMovedDueTo |
P116890
|
FINISHED |
| Object | security situation in Benghazi |
—
|
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: security situation in Benghazi | Statement: [House of Representatives (Libya), seatMovedDueTo, security situation in Benghazi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatMovedDueTo Context triple: [House of Representatives (Libya), seatMovedDueTo, security situation in Benghazi]
-
A.
movedSeatTo
Indicates that one entity changed another entity’s seating position from one place to another.
-
B.
seatVacatedBy
Indicates that a particular seat has been freed or relinquished as a result of an action performed by a specific entity.
-
C.
seatChangeComparedToPrevious
Indicates a change in the number of seats held by an entity compared to its previously held number of seats.
-
D.
seatLocation
Indicates the spatial position or placement of a seat relative to a reference point or environment.
-
E.
positionChange
Indicates a change in an entity’s spatial or positional state from one location or configuration to another.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e44cb0819096e09f8026ef8174 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:49 a.m.