Triple
T284999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman legion |
E5868
|
entity |
| Predicate | hasStandardBearer |
P10330
|
FINISHED |
| Object | signifer |
—
|
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: signifer | Statement: [Roman legion, hasStandardBearer, signifer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStandardBearer Context triple: [Roman legion, hasStandardBearer, signifer]
-
A.
hasNotableBearer
Indicates that an entity (such as a name, title, or identifier) is borne by at least one notable person or entity.
-
B.
hasNotableFieldOfBearers
Indicates that the entities share a significant or distinguished area of activity, expertise, or achievement associated with their bearers.
-
C.
usesStandard
Indicates that one entity adopts, follows, or operates according to a specified standard defined by another entity or reference.
-
D.
hasStandardizationBody
Indicates that an entity is associated with, governed by, or defined by a specific standards-setting organization or authority.
-
E.
hasSupported
Indicates that one entity has provided assistance, endorsement, or backing to another entity, either materially, emotionally, or through advocacy.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a2605b372c8190831570aa6532cc96 |
completed | Feb. 28, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69a25b7a8d148190aacdcc8ccb35c7f3 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a2605a3d988190a8872169fd8eb2e8 |
completed | Feb. 28, 2026, 3:26 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.