Triple
T2453770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rays |
E53768
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Rays |
E53768
|
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: Rays | Statement: [Rays, nickname, Rays]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rays Context triple: [Rays, nickname, Rays]
-
A.
Rays
chosen
Rays is the shortened nickname for the Tampa Bay Rays, a Major League Baseball team based in St. Petersburg, Florida.
-
B.
Barracuda
Barracuda is Seagate Technology’s long-running family of consumer and desktop hard disk drives known for high capacity and mainstream performance.
-
C.
Flying Fish
Flying Fish is a signature seafood restaurant at Disney’s BoardWalk in Walt Disney World, known for its upscale coastal cuisine and elegant, boardwalk-inspired atmosphere.
-
D.
Ika
Ika is a Sanskrit-derived word meaning “one” or “unity,” used in the Indonesian national motto “Bhinneka Tunggal Ika” to express the idea of oneness amid diversity.
-
E.
Tiburon
Tiburon is a small, affluent waterfront town in Marin County, California, known for its scenic views of San Francisco Bay and ferry access to nearby islands.
- 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_69ab495d227c8190b26ae6548eeb1019 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd0f7f85c8190a60970b6adb7fe80 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af17932530819097caefff366e2183 |
completed | March 9, 2026, 6:55 p.m. |
Created at: March 6, 2026, 9:44 p.m.