Triple
T1989784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harar Jugol |
E43224
|
entity |
| Predicate | urbanAreaSize |
P20546
|
FINISHED |
| Object | about 48 hectares |
—
|
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: about 48 hectares | Statement: [Harar Jugol, urbanAreaSize, about 48 hectares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: urbanAreaSize Context triple: [Harar Jugol, urbanAreaSize, about 48 hectares]
-
A.
cityArea
chosen
Indicates the total geographic area covered by a city.
-
B.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
C.
metroArea
Indicates that one location is part of, or belongs to, a specified metropolitan area.
-
D.
metroAreaSpans
Indicates that a metropolitan area extends across or covers multiple geographic or administrative regions.
-
E.
metropolitanAreaPopulationApproximate
Indicates that the predicate specifies an approximate total population size for a given metropolitan area.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8ee02dc81908fec9fd8df7a4f40 |
completed | March 7, 2026, 5:34 a.m. |
| PD | Predicate disambiguation | batch_69abb79ad6888190be99943a9c73cf3e |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.