Triple
T457505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FrontlineMakeshiftCamps |
E7264
|
entity |
| Predicate | durationOfUse |
P13716
|
FINISHED |
| Object | Intended for short-term use |
—
|
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: Intended for short-term use | Statement: [FrontlineMakeshiftCamps, durationOfUse, Intended for short-term use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: durationOfUse Context triple: [FrontlineMakeshiftCamps, durationOfUse, Intended for short-term use]
-
A.
yearOfUse
Indicates the specific year during which something was in use or actively utilized.
-
B.
periodOfMajorUse
Indicates the time span during which something was primarily or most intensively used.
-
C.
inUseSince
Indicates that an entity has been actively in use starting from a specified point in time.
-
D.
usedSince
Indicates that an entity has been in use starting from a specified point in time and continuing thereafter.
-
E.
usedDuring
Indicates that one entity is employed, applied, or active in the course of another entity’s process, event, or time period.
- 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_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. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.