Triple
T17051631
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PyTeal |
E413709
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | TEAL |
E1248468
|
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: TEAL | Statement: [PyTeal, relatedTo, TEAL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TEAL Context triple: [PyTeal, relatedTo, TEAL]
-
A.
TEAL
TEAL was the former international airline of New Zealand, operating trans-Tasman and Pacific routes before evolving into Air New Zealand.
-
B.
TEAL
chosen
TEAL is Algorand’s low-level, stack-based smart contract language used to define and execute logic on the blockchain.
-
C.
Teal
Teal is the entry-level membership tier in the WestJet Rewards loyalty program, offering basic benefits and the foundation for earning and redeeming WestJet dollars.
-
D.
Maroon
Maroon is a studio album by Canadian alternative rock band Barenaked Ladies, known for its witty lyrics and melodic pop-rock sound.
-
E.
Maroon
"Maroon" is a moody, synth-pop song by Taylor Swift that reflects on a past romance with vivid, color-themed imagery.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa26e84819098b41ae15618e813 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ed60d3481909c8144bcb01316a1 |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:34 a.m.