Triple
T4757967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Molly Bloom |
E105632
|
entity |
| Predicate | chapterCountOfMonologue |
P58317
|
FINISHED |
| Object | 8 sentences |
—
|
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: 8 sentences | Statement: [Molly Bloom, chapterCountOfMonologue, 8 sentences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chapterCountOfMonologue Context triple: [Molly Bloom, chapterCountOfMonologue, 8 sentences]
-
A.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
B.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
C.
numberOfNarrators
Indicates the quantity of distinct narrators associated with a given work or narrative.
-
D.
numberOfActs
Indicates the total count of discrete acts or actions associated with a given entity or event.
-
E.
storyNumber
Indicates the numerical identifier assigned to a specific story within a collection, sequence, or dataset.
- 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_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. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:20 p.m.