Triple
T457495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FrontlineMakeshiftCamps |
E7264
|
entity |
| Predicate | locatedInRelationTo |
P40
|
FINISHED |
| Object | Near front lines |
—
|
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: Near front lines | Statement: [FrontlineMakeshiftCamps, locatedInRelationTo, Near front lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInRelationTo Context triple: [FrontlineMakeshiftCamps, locatedInRelationTo, Near front lines]
-
A.
locatedIn
chosen
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
B.
locatedUnder
Indicates that one entity is positioned directly or generally beneath another entity in space.
-
C.
locatedAlong
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
-
D.
locatedBetween
Indicates that one entity is positioned spatially between two other reference entities.
-
E.
locatedAfter
Indicates that one entity is positioned later than another along a defined sequence, order, or spatial/temporal axis.
- 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_69a2e7e5c5bc8190a1dc8178218fba40 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efa3163081909acff040a22bd559 |
completed | Feb. 28, 2026, 1:37 p.m. |
| PD | Predicate disambiguation | batch_69a2ede614b88190be07425f5535f56d |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.