Triple
T3275757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francistown |
E68752
|
entity |
| Predicate | roleInBotswana |
P268
|
FINISHED |
| Object | major commercial center |
—
|
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: major commercial center | Statement: [Francistown, roleInBotswana, major commercial center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInBotswana Context triple: [Francistown, roleInBotswana, major commercial center]
-
A.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
B.
roleInLasVegas
Indicates that an entity holds or held a specific role, position, or function within the context of Las Vegas (such as in its government, organizations, events, or productions).
-
C.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
D.
roleInExpedition
Indicates the specific function, duty, or position an entity holds within the context of a particular expedition.
-
E.
role
chosen
Indicates the function, position, or responsibility that one entity holds in relation to another 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb0110f1c8190ae60708b686cbbf9 |
completed | March 8, 2026, 5:21 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:10 p.m.