Triple
T32920108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liling Xiang |
E842119
|
entity |
| Predicate | spokenInOrAround |
P67236
|
FINISHED |
| Object | Liling urban area |
—
|
NE NERFINISHED |
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: Liling urban area | Statement: [Liling Xiang, spokenInOrAround, Liling urban area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenInOrAround Context triple: [Liling Xiang, spokenInOrAround, Liling urban area]
-
A.
isSpokenAround
chosen
Indicates that something (such as a language, phrase, or expression) is commonly spoken in the vicinity of, or within the general area surrounding, a particular place or entity.
-
B.
spokenInLocality
Indicates that a language, dialect, or speech form is used or spoken within a specific locality or geographic area.
-
C.
possiblySpokenAt
Indicates that an utterance or speech event may have occurred at a particular time or location, but this association is uncertain or not definitively confirmed.
-
D.
spokenNear
Indicates that one entity spoke in close physical proximity to another entity or location.
-
E.
spokenOfAs
Indicates that one entity is referred to, characterized, or talked about in a particular way by another entity or within a given context.
- 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_69f3494779388190a5d3e97f92278be2 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6d74b20a48190900dda1014cc13a8 |
completed | May 3, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69f6d26f27dc8190ae426a3e1573933e |
completed | May 3, 2026, 4:43 a.m. |
Created at: May 1, 2026, 1:19 a.m.