Triple
T36411788
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greve in Chianti |
E896897
|
entity |
| Predicate | hasSurroundingLocalities |
P129318
|
FINISHED |
| Object | hamlets |
—
|
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: hamlets | Statement: [Greve in Chianti, hasSurroundingLocalities, hamlets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurroundingLocalities Context triple: [Greve in Chianti, hasSurroundingLocalities, hamlets]
-
A.
hasNeighbouringLocality
Indicates that one locality is geographically adjacent to or directly borders another locality.
-
B.
hasLocalities
chosen
Indicates that an entity is associated with, contains, or is linked to one or more specific geographic or administrative local areas.
-
C.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
D.
hasMultipleLocalities
Indicates that an entity is associated with more than one locality or geographic area.
-
E.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
- 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_69f76e54ce408190849acc3f7758937c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a001540d4f881908a4688881875e774 |
completed | May 10, 2026, 5:18 a.m. |
| PD | Predicate disambiguation | batch_6a0014a8cdd88190a67a90a2df2c5e18 |
completed | May 10, 2026, 5:16 a.m. |
Created at: May 3, 2026, 4:10 p.m.