Triple
T32752407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Hawamim |
E837531
|
entity |
| Predicate | firstChapterNumber |
P42626
|
FINISHED |
| Object | 40 |
—
|
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: 40 | Statement: [Al-Hawamim, firstChapterNumber, 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstChapterNumber Context triple: [Al-Hawamim, firstChapterNumber, 40]
-
A.
chapterNumber
Indicates the specific ordinal position a chapter occupies within a larger ordered work, such as a book or document.
-
B.
beginsAtChapter
Indicates that an entity (such as a section, event, or reference) starts or first occurs at a specified chapter in a structured work.
-
C.
firstAppearanceChapter
chosen
Indicates the chapter in which an entity (such as a character, item, or concept) is first introduced or appears in a work.
-
D.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
E.
chapterOn
Indicates that one entity (typically a chapter) is about, discusses, or focuses on the subject represented by another entity.
- 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_69f34937f97c8190b7f84bea045df3ae |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:12 a.m.