Triple
T4360503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Women's Land Army |
E98648
|
entity |
| Predicate | uniformIncluded |
P44882
|
FINISHED |
| Object | green jumper |
—
|
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: green jumper | Statement: [Women's Land Army, uniformIncluded, green jumper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformIncluded Context triple: [Women's Land Army, uniformIncluded, green jumper]
-
A.
formerlyIncluded
Indicates that an entity was previously part of, contained in, or a member of another entity, but is no longer included.
-
B.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
-
C.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
D.
traditionallyIncludes
chosen
Indicates that something customarily or historically contains or incorporates something else as a standard or expected part.
-
E.
isFrequentlyIncludedIn
Indicates that something is regularly or commonly contained or made part of something else.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351e3220881909dc9d02ab024abf5 |
completed | March 12, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:16 p.m.