Triple
T30799322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faneromeni Church |
E784320
|
entity |
| Predicate | hasSquareNamedAfter |
P137525
|
FINISHED |
| Object | Faneromeni Square |
—
|
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: Faneromeni Square | Statement: [Faneromeni Church, hasSquareNamedAfter, Faneromeni Square]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSquareNamedAfter Context triple: [Faneromeni Church, hasSquareNamedAfter, Faneromeni Square]
-
A.
squareNamedAfter
chosen
Indicates that a public square is named in honor of, or derived its name from, a particular person, place, event, or entity.
-
B.
hasSymbolNamedAfter
Indicates that one entity has a symbol whose name is derived from or dedicated to another entity.
-
C.
hasOpeningNamedAfter
Indicates that an opening (such as in a game, work, or structure) is named after a particular entity.
-
D.
hasCharacterNamedAfter
Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
-
E.
hasNaming
Indicates that one entity assigns, bears, or is associated with a specific name or designation provided by another entity.
- 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_69f224b3a7ec819096939414d103e31e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6903998008190a77f8503d88c50d8 |
completed | May 3, 2026, midnight |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:42 p.m.