Triple
T150490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Knights and Ladies |
E3418
|
entity |
| Predicate | precedenceInUK |
P1616
|
FINISHED |
| Object | highest order of chivalry in the United Kingdom |
—
|
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: highest order of chivalry in the United Kingdom | Statement: [Royal Knights and Ladies, precedenceInUK, highest order of chivalry in the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: precedenceInUK Context triple: [Royal Knights and Ladies, precedenceInUK, highest order of chivalry in the United Kingdom]
-
A.
orderPrecedence
Indicates that one entity must come before another in a defined sequence or priority order.
-
B.
confersPrecedenceIn
chosen
Indicates that one entity is granted higher priority, rank, or standing over another within a specified context or domain.
-
C.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
D.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
E.
precedentFor
Indicates that one situation, decision, or case serves as an authoritative example or basis for deciding or interpreting another.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580dda148190a522e0ac276d5f33 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.