Triple
T24031344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyde Park 7 July Memorial |
E595113
|
entity |
| Predicate | hasNumberOfStelae |
P9825
|
FINISHED |
| Object | 52 |
—
|
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: 52 | Statement: [Hyde Park 7 July Memorial, hasNumberOfStelae, 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfStelae Context triple: [Hyde Park 7 July Memorial, hasNumberOfStelae, 52]
-
A.
numberOfStelae
chosen
Indicates the quantity of stelae associated with a given entity or context.
-
B.
hasTallestStela
Indicates that one entity possesses or is associated with the tallest stela in comparison to other relevant entities.
-
C.
hasStoneMonument
Indicates that one entity possesses, contains, or features a stone monument associated with it.
-
D.
numberOfIndividualGeoglyphsApprox
Indicates an approximate count of distinct individual geoglyphs associated with a given subject.
-
E.
hasRockCarvingsFrom
Indicates that something contains or features rock carvings that originate from a specified source, place, or period.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d7709e5881908f5d4c0dd9f818c9 |
completed | April 29, 2026, 10:03 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:55 p.m.