Triple
T10611515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pagan |
E276018
|
entity |
| Predicate | numberOfMonumentsApproximate |
P32446
|
FINISHED |
| Object | over 2000 surviving monuments |
—
|
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: over 2000 surviving monuments | Statement: [Pagan, numberOfMonumentsApproximate, over 2000 surviving monuments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMonumentsApproximate Context triple: [Pagan, numberOfMonumentsApproximate, over 2000 surviving monuments]
-
A.
hasNumberOfMonuments
chosen
Indicates the specific count of monuments associated with or present in a given entity.
-
B.
hasNumberOfMuseums
Indicates the quantity of museums associated with a given entity.
-
C.
otherMonuments
Indicates that there exists a relationship between an entity and additional monuments that are associated with or related to it in some relevant way.
-
D.
monumentGroup
Indicates that one monument belongs to, or is categorized within, a specific group or collection of monuments.
-
E.
originalMonumentsFrom
Indicates that certain monuments were originally created, erected, or located in a specified place or source region.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df5a1450819082ad445712fb7868 |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7a223c8190854409d76368f3e8 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 7:33 p.m.