Triple
T33003975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Worshipful Company of Security Professionals |
E844443
|
entity |
| Predicate | becameCompanyWithoutLivery |
P175896
|
FINISHED |
| Object | 2000 |
—
|
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: 2000 | Statement: [Worshipful Company of Security Professionals, becameCompanyWithoutLivery, 2000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: becameCompanyWithoutLivery Context triple: [Worshipful Company of Security Professionals, becameCompanyWithoutLivery, 2000]
-
A.
hasLivery
Indicates that one entity bears or displays the distinctive colors, markings, or branding (livery) associated with another entity.
-
B.
liveryInspiredBy
Indicates that one livery’s design, colors, or overall appearance is based on, influenced by, or pays homage to another livery.
-
C.
liveryFeature
Indicates a characteristic or design element that is part of a specific livery or external appearance scheme.
-
D.
liveryColors
Indicates the specific set of colors used as the official or characteristic color scheme associated with an entity (such as a brand, organization, or vehicle).
-
E.
hasFormerLogo
Indicates that an entity is associated with a logo it used in the past but no longer uses.
- 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_69f3494e59f08190b9127c693e5c7e8f |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69f6d749e7f081909c8196898c4191ad |
completed | May 3, 2026, 5:04 a.m. |
Created at: May 1, 2026, 1:23 a.m.