Triple
T19497367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lang Toun |
E487804
|
entity |
| Predicate | refersToShape |
P123833
|
FINISHED |
| Object | elongated urban settlement |
—
|
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: elongated urban settlement | Statement: [Lang Toun, refersToShape, elongated urban settlement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToShape Context triple: [Lang Toun, refersToShape, elongated urban settlement]
-
A.
refersToPosition
Indicates that one entity makes reference to, or is associated with, a specific position or location of another entity.
-
B.
isReferencePointFor
Indicates that one entity serves as a positional or conceptual basis used to locate, measure, or interpret another entity.
-
C.
namedAfterShape
chosen
Indicates that one entity has been given a name based on the geometric or physical shape of another entity.
-
D.
refersToLocation
Indicates that one entity designates, points to, or identifies a specific location associated with it.
-
E.
seeksToShape
Indicates an entity’s intention or effort to influence, mold, or determine the form, direction, or outcome of another entity or situation.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e634924e24819085cd61ba33c84570 |
completed | April 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:40 p.m.