Triple
T20292384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rome Italy Temple |
E510057
|
entity |
| Predicate | templeNumberInCountry |
P113872
|
FINISHED |
| Object | 1 in Italy |
—
|
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: 1 in Italy | Statement: [Rome Italy Temple, templeNumberInCountry, 1 in Italy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: templeNumberInCountry Context triple: [Rome Italy Temple, templeNumberInCountry, 1 in Italy]
-
A.
pilgrimageTempleCount
Indicates the number of temples associated with or visited during a particular pilgrimage.
-
B.
hasTempleCount
Indicates that an entity is associated with a specified number of temples.
-
C.
isNumberedTempleOf
chosen
Indicates that one entity is a specific, designated temple identified by a particular number within a series or system associated with another entity.
-
D.
majorTempleLocation
Indicates that a major temple associated with an entity is located at a specified place.
-
E.
templeType
Indicates the specific category or classification of a temple in terms of its form, function, or religious/architectural style.
- 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_69e0b4c652388190b782cad965e5a098 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e677024de08190bfa54ae26b5486d1 |
completed | April 20, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:12 a.m.