Triple
T768378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NV |
E16223
|
entity |
| Predicate | formatExample |
P12958
|
FINISHED |
| Object | Reno, NV 89501 |
—
|
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: Reno, NV 89501 | Statement: [NV, formatExample, Reno, NV 89501]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formatExample Context triple: [NV, formatExample, Reno, NV 89501]
-
A.
format
Indicates the specific arrangement, structure, or presentation style in which something is organized or expressed.
-
B.
formatBefore
Indicates that one item’s format or formatting must occur or be applied prior to another item’s format or formatting.
-
C.
formatAfter
Indicates that one entity’s format or structural arrangement is derived from, follows, or is applied subsequent to another entity’s format.
-
D.
formatDSTExample
chosen
Indicates that an example is provided to illustrate how something should be formatted in a dialog state tracking (DST) context.
-
E.
typicalForm
Indicates that one entity represents the standard, characteristic, or most common form or shape in which another entity typically appears or is realized.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a765ba688190ab328bb159583077 |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a5074c788190a74fc20ad24e2d26 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.