Triple
T496773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 NWSL Championship |
E10310
|
entity |
| Predicate | hostCity |
P1798
|
FINISHED |
| Object | Orlando |
E11265
|
NE 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: Orlando | Statement: [2017 NWSL Championship, hostCity, Orlando]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orlando Context triple: [2017 NWSL Championship, hostCity, Orlando]
-
A.
Orlando
chosen
Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
-
B.
Jacksonville, Florida
Jacksonville, Florida is a major city in northeastern Florida known for its extensive riverfront, large land area, and role as a regional economic and transportation hub.
-
C.
Kissimmee, Florida
Kissimmee, Florida is a central Florida city in Osceola County known for its proximity to major Orlando-area theme parks and tourist attractions.
-
D.
St. Petersburg, Florida
St. Petersburg, Florida is a coastal city on Florida’s Gulf Coast known for its sunny climate, beaches, and vibrant arts and cultural scene.
-
E.
Miami
Miami is a major coastal city in southeastern Florida known for its vibrant nightlife, diverse culture, and role as a global center for finance, tourism, and international trade.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f116f1b4819082f88d6c747368ae |
completed | Feb. 28, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a57b51a58481909d8e602b3fe3c68c |
completed | March 2, 2026, 11:58 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.