Triple
T16676999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garbage |
E405236
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Queer |
E308204
|
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: Queer | Statement: [Garbage, notableSong, Queer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queer Context triple: [Garbage, notableSong, Queer]
-
A.
Queer
chosen
Queer is a semi-autobiographical novel by William S. Burroughs that explores themes of homosexuality, addiction, and alienation in postwar Mexico City.
-
B.
Queer
"Queer" is a short story by Sherwood Anderson that appears as one of the interconnected tales in his 1919 collection *Winesburg, Ohio*.
-
C.
Gay
Gay is a common English surname borne by various notable individuals across fields such as academia, politics, and the arts.
-
D.
queer theory
Queer theory is a critical intellectual movement that challenges normative ideas about gender, sexuality, and identity, drawing on poststructuralist and feminist thought to analyze how power shapes social and cultural norms.
-
E.
GAY
GAY is the IATA airport code for Gaya Airport, serving the city of Gaya in the Indian state of Bihar.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6c805c81909fbe4fcb20eedbe1 |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3c79888190b6ddd55b91d97183 |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.