Triple
T13820454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Decapolis |
E332120
|
entity |
| Predicate | hasNumberOfCities |
P101584
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Decapolis, hasNumberOfCities, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfCities Context triple: [Decapolis, hasNumberOfCities, 10]
-
A.
hasNumberOfComponentCities
chosen
Indicates the relationship that specifies how many component cities are contained within or associated with a given entity.
-
B.
hasNumberOfMunicipalities
Indicates the relationship that specifies how many municipalities are associated with or contained within a given administrative or geographic entity.
-
C.
hasNumberOfProvinces
Indicates the total count of provinces associated with a given entity.
-
D.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
-
E.
hasNumberOfImperialCities
Indicates the relationship between an entity and the count of imperial cities associated with or contained within it.
- 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_69d81c59f8808190a851bc56afdc55e9 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0282d4d08190b754cda7683408c4 |
completed | April 14, 2026, 9:01 a.m. |
| PD | Predicate disambiguation | batch_69dbc862e9608190bd8a3d883959b7e4 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:12 p.m.