Triple
T4843595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Overton (place name) |
E108235
|
entity |
| Predicate | hasNamingPattern |
P8151
|
FINISHED |
| Object | topographic description plus Old English "tūn" |
—
|
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: topographic description plus Old English "tūn" | Statement: [Overton (place name), hasNamingPattern, topographic description plus Old English "tūn"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamingPattern Context triple: [Overton (place name), hasNamingPattern, topographic description plus Old English "tūn"]
-
A.
hasPattern
chosen
Indicates that one entity exhibits, follows, or is characterized by a specific recurring form, structure, or design defined by another entity.
-
B.
usesNamingSystem
Indicates that one entity adopts or applies a particular naming system or convention to identify or label other entities.
-
C.
namingConventionType
Indicates the specific style or set of rules used for naming entities or elements in a given context.
-
D.
hasStreetNamingPattern
Indicates that there is a characteristic or systematic way in which streets are named in relation to a given entity.
-
E.
notationPattern
Indicates a recurring way in which something is symbolically represented or written, such as a consistent style or structure of notation used for an entity or concept.
- 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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e01872c81909607010c10538ad1 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2375a4819098e16acb982c8fab |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:25 p.m.