Triple
T33046610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Asiatic Vespers |
E845612
|
entity |
| Predicate | notableCityInvolved |
P81739
|
FINISHED |
| Object | Ephesus |
E50337
|
NE 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: Ephesus | Statement: [Asiatic Vespers, notableCityInvolved, Ephesus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableCityInvolved Context triple: [Asiatic Vespers, notableCityInvolved, Ephesus]
-
A.
notableCityOfOperation
Indicates that a city is a primary or particularly significant location where an entity conducts its operations or activities.
-
B.
notableCityInConflict
chosen
Indicates that a city is prominently involved or significantly affected in a particular conflict or war.
-
C.
notableCityIncluded
Indicates that a notable or significant city is contained within, or is part of, a larger geographic or administrative entity.
-
D.
notableInCity
Indicates that an entity is particularly prominent, recognized, or significant within a specific city.
-
E.
notableCitiesRepresented
Indicates that an entity includes or features certain cities as particularly important or prominently represented within it.
- F. None of above.
Provenance (4 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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a34e5181dc481908dc4eb3229d81399 |
completed | June 19, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:24 a.m.