Triple
T9753672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omnidroid |
E236501
|
entity |
| Predicate | purposeInFiction |
P80898
|
FINISHED |
| Object | to kill superheroes |
—
|
LITERAL 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: to kill superheroes | Statement: [Omnidroid, purposeInFiction, to kill superheroes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: purposeInFiction Context triple: [Omnidroid, purposeInFiction, to kill superheroes]
-
A.
literaryPurpose
Indicates the intended function, effect, or communicative goal that a text or passage is meant to achieve within a literary context.
-
B.
narrativePurpose
chosen
Indicates the role or function that something serves within the structure or progression of a narrative.
-
C.
purpose
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
D.
depictionPurpose
Indicates that one entity is depicted specifically for the purpose or function it serves in relation to another entity.
-
E.
fictionalUse
Indicates that one entity makes use of another within a fictional or imaginary context, rather than in real-world usage.
- F. None of above.
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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9fb01ad08190b2435fa505c622bc |
completed | April 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69cd03cc128c81908b84ef224f858b4e |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:24 p.m.