Triple
T11250783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MonstroCity: Rampage |
E266315
|
entity |
| Predicate | hasMonsterCollection |
P98700
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [MonstroCity: Rampage, hasMonsterCollection, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMonsterCollection Context triple: [MonstroCity: Rampage, hasMonsterCollection, true]
-
A.
hasAnimalCollection
Indicates that one entity possesses or maintains a collection or group of animals associated with it.
-
B.
hasMysterySet
Indicates that an entity possesses or includes a collection or configuration whose nature or details are unknown or intentionally concealed.
-
C.
hasColossiOf
Indicates that one entity possesses, contains, or is characterized by monumental statues or colossal figures associated with another entity.
-
D.
hasFictionalCollector
Indicates that an entity is associated with a fictional character who collects or curates it.
-
E.
hasMythicMotif
Indicates that one entity features, embodies, or is associated with a particular mythic motif found in the other entity.
- F. None of above. chosen
Provenance (4 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e93212448190b46b3799b0bdfa0f |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
| PDg | Predicate description generation | batch_69d796cf74308190a5b29d0dd82954a2 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:31 p.m.