Triple
T29761353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airy (lunar crater) |
E753778
|
entity |
| Predicate | honoursCountry |
P73887
|
FINISHED |
| Object | United Kingdom |
—
|
NE NERFINISHED |
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: United Kingdom | Statement: [Airy (lunar crater), honoursCountry, United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honoursCountry Context triple: [Airy (lunar crater), honoursCountry, United Kingdom]
-
A.
honoursMilitaryService
Indicates that one entity formally recognizes and pays tribute to the military service performed by another entity.
-
B.
honoursCivilianService
Indicates recognition or commemoration of an individual's non-military contributions or service to society.
-
C.
honourOf
Indicates that one entity is the source, bearer, or cause of another entity’s honor, prestige, or distinguished recognition.
-
D.
honorsCountry
chosen
Indicates that one entity formally recognizes, respects, or pays tribute to a particular country.
-
E.
honoursLegacyOf
Indicates that one entity actively preserves, respects, or celebrates the memory, values, or achievements of another entity from the past.
- 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_69f0ef827ff88190ade56e0b0846b713 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f673d041448190a414a19cf28b09d2 |
completed | May 2, 2026, 9:59 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 8:33 p.m.