Triple
T35626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Army Rangers |
E704
|
entity |
| Predicate | uniformDistinction |
P2337
|
FINISHED |
| Object | tan beret |
—
|
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: tan beret | Statement: [United States Army Rangers, uniformDistinction, tan beret]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformDistinction Context triple: [United States Army Rangers, uniformDistinction, tan beret]
-
A.
distribution
Indicates the act or pattern of giving, delivering, or spreading something from one source to multiple recipients or locations.
-
B.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
C.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
D.
defined
Indicates that one entity specifies, explains, or establishes the meaning, scope, or identity of another entity.
-
E.
divisionTitle
Indicates the formal name or title assigned to a specific division within a larger organization or structure.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24989c3308190af59dfae37cfc32f |
completed | Feb. 28, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69a24873e97c8190b9e4279e43b6de14 |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a24988d4688190b4584356ed7dea50 |
completed | Feb. 28, 2026, 1:48 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.