Triple
T19070310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spyridon Samaras |
E466772
|
entity |
| Predicate | composed |
P1142
|
FINISHED |
| Object | Tigra |
—
|
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: Tigra | Statement: [Spyridon Samaras, composed, Tigra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tigra Context triple: [Spyridon Samaras, composed, Tigra]
-
A.
Tigra
chosen
Tigra is an opera by Greek composer Spyridon Samaras, known for its late-Romantic style and contribution to early 20th-century Greek musical theater.
-
B.
Tigra
Tigra is a feline-themed Marvel Comics superheroine known for her enhanced agility, strength, and senses, as well as her long-standing membership in various Avengers teams.
-
C.
Tigerman
Tigerman is the surname of Stanley Tigerman, a notable American architect associated with postmodern design.
-
D.
Tigarah
Tigarah is a Japanese rapper and singer known for her eclectic blend of hip hop, baile funk, and electronic music.
-
E.
Tigar
Tigar is a Serbian tire manufacturer known for producing budget-friendly tires and rubber products, operating as a subsidiary of the Michelin Group.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19ea01c8190b9bb789da32f9a90 |
completed | April 20, 2026, 8:19 a.m. |
Created at: April 10, 2026, 12:04 p.m.