Triple
T4757958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molly Bloom |
E105632
|
entity |
| Predicate | monologueLocation |
P11537
|
FINISHED |
| Object | Penelope episode |
—
|
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: Penelope episode | Statement: [Molly Bloom, monologueLocation, Penelope episode]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: monologueLocation Context triple: [Molly Bloom, monologueLocation, Penelope episode]
-
A.
locationOfDiscourse
chosen
Indicates the place or setting where a particular discourse, conversation, or communicative event occurs.
-
B.
placeOfSetting
Indicates the location or environment where an event, scene, or situation takes place.
-
C.
subjectLocation
Indicates that one entity is located at, in, or near the place or position specified by another entity.
-
D.
mainLocation
Indicates that one entity serves as the primary or central location associated with another entity.
-
E.
dialoguePosition
Indicates the relative placement or ordering of an utterance or turn within a dialogue or conversational sequence.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6225c9488190afee5bb3619d0365 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.