Triple
T12982738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort End |
E321691
|
entity |
| Predicate | hasNamedEndCounterpart |
P94153
|
FINISHED |
| Object | City End |
—
|
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: City End | Statement: [Fort End, hasNamedEndCounterpart, City End]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamedEndCounterpart Context triple: [Fort End, hasNamedEndCounterpart, City End]
-
A.
hasCounterpart
Indicates that one entity corresponds to, matches, or serves as an equivalent or parallel version of another entity.
-
B.
counterpartEnglishName
Indicates that an entity has a corresponding counterpart whose name is given in English.
-
C.
hasOpeningNamedAfter
Indicates that an opening (such as in a game, work, or structure) is named after a particular entity.
-
D.
counterpartRelation
chosen
Indicates a reciprocal relationship where two entities serve as corresponding or equivalent counterparts to each other in a given context.
-
E.
hasEnd
Indicates that one entity serves as the terminal point, boundary, or conclusion of another entity or process.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:39 p.m.