Triple
T29196696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Bukamal |
E740143
|
entity |
| Predicate | nearbyCityAcrossBorderCountry |
P148850
|
FINISHED |
| Object | Iraq |
—
|
NE NERFINISHED |
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: Iraq | Statement: [Al-Bukamal, nearbyCityAcrossBorderCountry, Iraq]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyCityAcrossBorderCountry Context triple: [Al-Bukamal, nearbyCityAcrossBorderCountry, Iraq]
-
A.
borderingCountryNearby
Indicates that one country is geographically close to, but does not necessarily share a direct land border with, another country.
-
B.
nearestForeignCity
chosen
Indicates that one city is the geographically closest city located in a different country relative to another city.
-
C.
countryBorderProximity
Indicates that one country is geographically close to or directly bordering another country.
-
D.
oppositeTownAcrossBorder
Indicates that one town is located directly across a border from another town, positioned as its opposite counterpart.
-
E.
isNeighboringCityOf
Indicates that one city is geographically adjacent to or directly borders another city.
- 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_69f07cb8033c8190b8807e219a14333d |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: April 28, 2026, 12:04 p.m.