Triple
T15837551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | al-Madina al-Fadila |
E384021
|
entity |
| Predicate | comparesCityTo |
P119845
|
FINISHED |
| Object | human body |
—
|
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: human body | Statement: [al-Madina al-Fadila, comparesCityTo, human body]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comparesCityTo Context triple: [al-Madina al-Fadila, comparesCityTo, human body]
-
A.
city2
Indicates a relationship where one entity is identified as a city associated with, located in, or otherwise linked to another entity.
-
B.
cityOfReference
Indicates that one entity serves as the primary or official city associated with, or used as a reference point for, another entity.
-
C.
city1
Indicates that the subject is classified as a city.
-
D.
isCityOf
Indicates that one entity is a city that belongs to, is located within, or is administratively part of another entity (such as a country, state, or region).
-
E.
selectionCity
Indicates that a particular city has been chosen or designated from among multiple possible cities.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e3d48c8190ad0d0af89d062101 |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005418f588190824d91ff7974dada |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e007647f908190adb178c68c7bb7cf |
completed | April 15, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:49 a.m.