Triple
T37013409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seattle Regional 4 |
E916009
|
entity |
| Predicate | numberOfRegionalSitesInTournament |
P205694
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Seattle Regional 4, numberOfRegionalSitesInTournament, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRegionalSitesInTournament Context triple: [Seattle Regional 4, numberOfRegionalSitesInTournament, 4]
-
A.
numberOfRegionalBracketsInTournament
Indicates the total count of distinct regional brackets that are included within a given tournament.
-
B.
totalTeamsInRegionals
Indicates the total number of teams that participate in the regional-level stage of a competition or event.
-
C.
regionTournament
Indicates a tournament that is held within, or associated with, a specific geographic or administrative region.
-
D.
numberOfTournaments
Indicates the total count of tournaments associated with or participated in by an entity.
-
E.
roundsPerTournament
Indicates the number of rounds that occur within a single tournament.
- F. None of above. chosen
Provenance (4 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_69f76e90ed548190b187d2475f5c807d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:14 p.m.