Triple
T21159569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayley |
E521401
|
entity |
| Predicate | hasOriginFromToponym |
P97773
|
FINISHED |
| Object | English place names ending in -ley |
—
|
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: English place names ending in -ley | Statement: [Hayley, hasOriginFromToponym, English place names ending in -ley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOriginFromToponym Context triple: [Hayley, hasOriginFromToponym, English place names ending in -ley]
-
A.
hasOriginToponym
chosen
Indicates that something originates from, or is derived from, the place denoted by a specific toponym (geographical name).
-
B.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
C.
hasTypeOfToponym
Indicates that one entity is classified as a specific type or category of toponym (place name) in relation to another entity.
-
D.
includesToponym
Indicates that one entity contains or references a place name (toponym) associated with another entity.
-
E.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
- 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_69e0b50d1ea481909c07e63c3ead9316 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7252e9ef481908f4904c535f3da8b |
completed | April 21, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69e5f5f8a5bc819081918c7fa8e4496d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 2:59 p.m.