Triple
T3713864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amphissa |
E81478
|
entity |
| Predicate | typeOfLocation |
P16688
|
FINISHED |
| Object | fortified city |
—
|
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: fortified city | Statement: [Amphissa, typeOfLocation, fortified city]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfLocation Context triple: [Amphissa, typeOfLocation, fortified city]
-
A.
placeType
chosen
Indicates the type or category of place associated with an entity (e.g., city, park, building).
-
B.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
C.
typeLocality
Indicates the specific geographic location where a specimen or taxon was originally found and formally described.
-
D.
platformLocation
Indicates the spatial position or placement of a platform relative to a reference point or environment.
-
E.
arrivalLocationType
Indicates the type or category of place where an arrival occurs in the described relationship or event.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc9ccfad081908730ed15c6f87ce2 |
completed | March 8, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.