Triple
T29209047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vavuniya town |
E740496
|
entity |
| Predicate | locatedInFormerConflictRegion |
P34508
|
FINISHED |
| Object | Sri Lankan Civil War northern theatre |
—
|
NE NERFINISHED |
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: Sri Lankan Civil War northern theatre | Statement: [Vavuniya town, locatedInFormerConflictRegion, Sri Lankan Civil War northern theatre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInFormerConflictRegion Context triple: [Vavuniya town, locatedInFormerConflictRegion, Sri Lankan Civil War northern theatre]
-
A.
regionOfConflict
chosen
Indicates that a specified region is the location where a particular conflict or dispute takes place.
-
B.
locatedOnSideOfConflict
Indicates that an entity is positioned or aligned on a particular side or faction within a conflict.
-
C.
basedInDuringConflict
Indicates that an entity is located or headquartered in a particular place for the duration of a specified conflict or war.
-
D.
locatedInDisputedTerritory
Indicates that an entity is situated within a geographic area whose sovereignty or ownership is contested between two or more parties.
-
E.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
- 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_69f07cb974108190b7e86ca489a6ebb6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_6a000be59ad88190a6aa3a42c097796d |
completed | May 10, 2026, 4:39 a.m. |
| PD | Predicate disambiguation | batch_6a000ab6e9bc81908300b81d004e5921 |
completed | May 10, 2026, 4:33 a.m. |
Created at: April 28, 2026, 12:10 p.m.