Triple
T5010103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nine Billion Names of God |
E112596
|
entity |
| Predicate | hasTitleWordCount |
P7605
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [The Nine Billion Names of God, hasTitleWordCount, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleWordCount Context triple: [The Nine Billion Names of God, hasTitleWordCount, 6]
-
A.
containsTitle
Indicates that one entity includes or holds another entity’s title as part of its content or metadata.
-
B.
wordCount
chosen
Indicates the total number of words contained in a given text or linguistic unit.
-
C.
hasTitleSubject
Indicates that an entity has a specific subject or topic as the focus of its title.
-
D.
hasStandardLetterCount
Indicates that an entity’s associated text or label contains a number of letters that matches a predefined standard or expected count.
-
E.
hasNumberOfTerms
Indicates the quantity of distinct terms or elements associated with a given entity or expression.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730bdb208190bebd7f22839ab6e5 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.