Triple
T23468567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big A scoreboard structure |
E569162
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | The Big A |
—
|
NE NERFINISHED |
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: The Big A | Statement: [Big A scoreboard structure, alsoKnownAs, The Big A]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Big A Context triple: [Big A scoreboard structure, alsoKnownAs, The Big A]
-
A.
The Big A
The Big A is a major Thoroughbred horse racing venue located in Queens, New York City.
-
B.
The Big A
chosen
The Big A is the popular nickname for Angel Stadium of Anaheim, the longtime home ballpark of Major League Baseball’s Los Angeles Angels.
-
C.
The Big Store
The Big Store is a 1941 Marx Brothers comedy film featuring their trademark slapstick, wordplay, and musical numbers set in a chaotic department store.
-
D.
The Big N
The Big N is a large-scale abstract geometric painting by American artist Al Held, exemplifying his bold use of color, form, and spatial illusion.
-
E.
Big W
Big W is an Australian chain of discount department stores offering a wide range of affordable household goods, clothing, electronics, and everyday essentials.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6fd280c81908aae05f0851466eb |
completed | April 29, 2026, 6:36 a.m. |
Created at: April 17, 2026, 5:54 p.m.