Triple
T19447624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nevil |
E486522
|
entity |
| Predicate | hasLikelyToponymicOrigin |
P9174
|
FINISHED |
| Object | Norman place name Neville |
—
|
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: Norman place name Neville | Statement: [Nevil, hasLikelyToponymicOrigin, Norman place name Neville]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLikelyToponymicOrigin Context triple: [Nevil, hasLikelyToponymicOrigin, Norman place name Neville]
-
A.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
-
B.
hasOriginToponym
Indicates that something originates from, or is derived from, the place denoted by a specific toponym (geographical name).
-
C.
hasToponymicForm
chosen
Indicates that one entity is a toponymic (place-name-based) form or variant derived from another entity.
-
D.
hasToponymicMotivation
Indicates that something is motivated, derived, or named based on a place name (toponym).
-
E.
hasEthnolinguisticOriginOfToponym
Indicates that a toponym (place name) originates from or is derived from a particular ethnolinguistic group or language.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338b25d88190bc137a411576c73f |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.