Triple
T30641383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Markazi Province |
E779987
|
entity |
| Predicate | areaRankInIran |
P169647
|
FINISHED |
| Object | among smaller provinces by area |
—
|
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: among smaller provinces by area | Statement: [Markazi Province, areaRankInIran, among smaller provinces by area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaRankInIran Context triple: [Markazi Province, areaRankInIran, among smaller provinces by area]
-
A.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
B.
hasCityRank
Indicates that a city holds a particular rank or position within a defined ordering or hierarchy (such as size, importance, or administrative level).
-
C.
areaRankInPakistan
Indicates the relative position of an entity when all entities in Pakistan are ordered by their area size.
-
D.
areaRankInIndia
Indicates the relative position of an entity when all entities in India are ordered by their area size.
-
E.
hasPopulationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
- F. None of above. chosen
Provenance (4 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a557e308190a55aa6958b6d012e |
completed | May 2, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 29, 2026, 8:29 p.m.