Triple
T23803540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Countess Spencer |
E589637
|
entity |
| Predicate | equivalentContinentalRank |
P126997
|
FINISHED |
| Object | comtesse |
—
|
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: comtesse | Statement: [Countess Spencer, equivalentContinentalRank, comtesse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentContinentalRank Context triple: [Countess Spencer, equivalentContinentalRank, comtesse]
-
A.
traditionalContinentalEquivalent
chosen
Indicates that one entity is the traditional continental (non-UK/US) counterpart or equivalent of another entity in role, function, or classification.
-
B.
rankEquivalent
Indicates that two entities hold the same rank or hierarchical level within a given ordering or classification system.
-
C.
rankingInEurope
Indicates the position or level an entity holds within a comparative ranking limited to Europe.
-
D.
countryEquivalent
Indicates that two country entities are considered equivalent or represent the same country in the given context.
-
E.
continentRank
Indicates the relative ordering or position of a continent within a ranked list of continents according to some specified criterion.
- 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_69e25d19fecc8190a5cf39bbb18d5d7f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c750048c8190899ff611df35b361 |
completed | April 29, 2026, 8:54 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:54 p.m.