Triple
T33118535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dorian |
E847525
|
entity |
| Predicate | replacedModelLine |
P194089
|
FINISHED |
| Object | MX-series police androids |
—
|
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: MX-series police androids | Statement: [Dorian, replacedModelLine, MX-series police androids]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: replacedModelLine Context triple: [Dorian, replacedModelLine, MX-series police androids]
-
A.
replacedEarlierModel
Indicates that one entity has taken the place of another entity that existed or was in use previously.
-
B.
lineReplaced
Indicates that one line has been substituted or superseded by another line, typically in a versioning, editing, or modification context.
-
C.
revisedModel
Indicates that an existing model has been updated or modified from its previous version.
-
D.
firstModelLineOf
Indicates that one entity is the first line of a model or modeling construct associated with another entity.
-
E.
hasModelLine
Indicates that an item, product, or entity belongs to or is associated with a particular model line or series.
- 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_69f3495751a081909850af5843da40dc |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd5f29b1988190877764ef2a399c7f |
completed | May 8, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69fd5e30194c819085b5ce586122ab37 |
completed | May 8, 2026, 3:53 a.m. |
| PDg | Predicate description generation | batch_69fd5f2903a48190ac4b718bff99c6cf |
completed | May 8, 2026, 3:57 a.m. |
Created at: May 1, 2026, 1:27 a.m.