Triple
T12341046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eleanor Cross at Geddington |
E294224
|
entity |
| Predicate | numberOfEleanorCrossSeries |
P11324
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Eleanor Cross at Geddington, numberOfEleanorCrossSeries, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEleanorCrossSeries Context triple: [Eleanor Cross at Geddington, numberOfEleanorCrossSeries, 12]
-
A.
numberOfSeries
chosen
Indicates the total count of distinct series associated with or contained within a given entity.
-
B.
bookSeriesEndYear
Indicates the calendar year in which a book series was concluded or last published.
-
C.
hasSeriesNumber
Indicates that an entity is assigned a specific ordinal or sequence number within a series or ordered set.
-
D.
seriesOf
Indicates that one entity is a sequence or ordered set of related items, events, or parts that collectively form or belong to another entity.
-
E.
numberOfEditions
Indicates the total count of distinct editions associated with a given 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7758dc8190bbc6a9ad00b01dce |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ecb5efc819086a3530282278bb1 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.