Triple
T2227060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomb Guard |
E48675
|
entity |
| Predicate | uniformStandard |
P1587
|
FINISHED |
| Object | highly precise dress uniform requirements |
—
|
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: highly precise dress uniform requirements | Statement: [Tomb Guard, uniformStandard, highly precise dress uniform requirements]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uniformStandard Context triple: [Tomb Guard, uniformStandard, highly precise dress uniform requirements]
-
A.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
B.
standardNumber
Indicates that an entity is associated with a canonical or officially recognized reference number used for identification or classification.
-
C.
usesStandard
chosen
Indicates that one entity adopts, follows, or operates according to a specified standard defined by another entity or reference.
-
D.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
E.
firstStandardized
Indicates that an entity is the earliest or primary instance to which a standard or uniform specification has been first applied among comparable entities.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0411e388190b35e82ad6688bfe3 |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdadbb0c8190b3a1ede31b8acbfa |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.