Triple
T12083472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1st Tverskaya-Yamskaya Street |
E287742
|
entity |
| Predicate | hasOrdinalNumberInName |
P4901
|
FINISHED |
| Object | 1st |
—
|
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: 1st | Statement: [1st Tverskaya-Yamskaya Street, hasOrdinalNumberInName, 1st]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrdinalNumberInName Context triple: [1st Tverskaya-Yamskaya Street, hasOrdinalNumberInName, 1st]
-
A.
ordinalNumber
chosen
Indicates the position or rank of an entity within an ordered sequence (e.g., first, second, third).
-
B.
hasNotableBearerOrdinalNumber
Indicates that an entity is associated with a notable bearer identified by a specific ordinal position (e.g., first, second, third) among others with the same name or title.
-
C.
isNumberedBy
Indicates that an entity is assigned, identified, or organized by a specific number or numbering scheme.
-
D.
hasNumeral
Indicates that one entity is associated with a numeral representation or numeric symbol of another entity.
-
E.
hasOrdinalSeries
Indicates that one entity belongs to, or is positioned within, an ordered sequence or series relative to other entities.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.