Triple
T13369904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krypton (TV series) |
E319033
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Seg-El |
E1036139
|
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: Seg-El | Statement: [Krypton (TV series), character, Seg-El]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seg-El Context triple: [Krypton (TV series), character, Seg-El]
-
A.
Seg-El
chosen
Seg-El is the protagonist of the TV series "Krypton," a young Kryptonian and grandfather of Superman who fights to restore his family's honor and save his planet's future.
-
B.
Sema Naga
Sema Naga are an indigenous Naga ethnic community of northeastern India known for their distinct language, rich warrior traditions, and vibrant festivals.
-
C.
Seif
Seif is a family name most notably associated with Riad Seif, a prominent Syrian businessman and opposition politician.
-
D.
Soor
Soor is a small river in eastern Belgium that flows through the High Fens region before joining the Vesdre.
-
E.
Seini
Seini is a small town in northwestern Romania, known for its industrial activities and location near the Lăpuș River in Maramureș County.
- 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_69d806b7bbac8190b85278c87fa7aff3 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd79184819088948cd38d10a4a5 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7306a4c688190bfbf5e695b2fd5e5 |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:33 p.m.