Triple
T15683334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heather Kadin |
E377633
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Scorpion |
E587270
|
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: Scorpion | Statement: [Heather Kadin, notableWork, Scorpion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scorpion Context triple: [Heather Kadin, notableWork, Scorpion]
-
A.
Scorpion
"Scorpion" is a highly acclaimed two-part Star Trek: Voyager episode that introduces the Borg's conflict with Species 8472 and marks Seven of Nine's entry into the series.
-
B.
Scorpion
Scorpion is a thrill ride attraction in the Pantopia section of Busch Gardens Tampa Bay, known for its intense looping roller coaster experience.
-
C.
Scorpion
chosen
Scorpion is an American television drama series that follows a team of brilliant misfits who tackle high-tech threats for the U.S. government.
-
D.
Scorpion
Scorpion is a vengeful undead ninja and one of the most iconic and enduring fighters in the Mortal Kombat video game series.
-
E.
Scorpion
Scorpion is a line of Pirelli tires designed primarily for SUVs, crossovers, and light trucks, emphasizing performance, safety, and versatility on various terrains.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f31b5b881908e46ecd9fc6048ab |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee4c8688190ae2fefb56171161a |
completed | May 9, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:17 a.m.