Triple
T3860581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark-3 |
E90124
|
entity |
| Predicate | inFictionalTimeline |
P18945
|
FINISHED |
| Object | deployed during height of Kaiju War |
—
|
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: deployed during height of Kaiju War | Statement: [Mark-3, inFictionalTimeline, deployed during height of Kaiju War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inFictionalTimeline Context triple: [Mark-3, inFictionalTimeline, deployed during height of Kaiju War]
-
A.
fictionalEra
chosen
Indicates the time period or age within a fictional or imaginary setting in which an entity exists or an event occurs.
-
B.
fictionalAge
Indicates the age attributed to an entity within a fictional or narrative context, rather than its real-world age.
-
C.
fictionalHistoryFeature
Indicates a relationship where something is a notable element or aspect within the fictional history or backstory of another entity.
-
D.
fictionalUniverseCreated
Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
-
E.
fictionalUniverse
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec212a1c8190aba6311630c3fd3e |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.