Triple
T26810755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archaeological Museum of Pythagoreio |
E671985
|
entity |
| Predicate | locatedInAncientCityArea |
P24406
|
FINISHED |
| Object | ancient Samos |
—
|
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: ancient Samos | Statement: [Archaeological Museum of Pythagoreio, locatedInAncientCityArea, ancient Samos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInAncientCityArea Context triple: [Archaeological Museum of Pythagoreio, locatedInAncientCityArea, ancient Samos]
-
A.
locatedInAncientCity
chosen
Indicates that an entity is situated within the boundaries or domain of an ancient city.
-
B.
relatesToAncientCity
Indicates a relationship or connection between an entity and an ancient city, such as origin, location, influence, or relevance.
-
C.
ancientCity
Indicates that the subject is a historically old or long-established city, typically originating from ancient times.
-
D.
ancientDistrictOf
Indicates that one entity is an ancient or historical district that forms part of, or is located within, another entity.
-
E.
hasNearbyAncientCity
Indicates that one entity is located close to another entity that is classified as an ancient city.
- 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_69eeb3225a3c8190aaf6746efeded2f3 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
Created at: April 27, 2026, 4:29 a.m.