Triple
T14553542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anchor & Braille |
E341479
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Tension |
E740923
|
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: Tension | Statement: [Anchor & Braille, notableWork, Tension]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tension Context triple: [Anchor & Braille, notableWork, Tension]
-
A.
Tension
"Tension" is a 2023 dance-pop album by Australian singer Kylie Minogue, known for its upbeat production and the hit single "Padam Padam."
-
B.
Tension
chosen
"Tension" is a song by Fergie from her 2017 album *Double Dutchess*, blending pop and hip-hop elements with a confident, club-ready vibe.
-
C.
S.T.R.E.S.S.
S.T.R.E.S.S. is a notable track from the project "Room for Improvement," recognized for its introspective lyrics and early showcase of the artist’s developing style.
-
D.
Tense
Tense is a seminal linguistic study by Bernard Comrie that analyzes how languages grammatically encode time distinctions in verbs.
-
E.
Angoisse
Angoisse is a prose poem by Arthur Rimbaud, included in his influential collection *Les Illuminations*, known for its vivid, hallucinatory imagery and exploration of existential dread.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f00cec8190a7b6482d18b9a216 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd8ab9a5ac81908779a3c8701353fa |
completed | May 8, 2026, 7:03 a.m. |
Created at: April 10, 2026, 1:23 a.m.