Triple
T6958935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sector 2 |
E161317
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Obor |
E629465
|
NE 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: Obor | Statement: [Sector 2, contains, Obor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Obor Context triple: [Sector 2, contains, Obor]
-
A.
Obor
chosen
Obor is a Bucharest Metro station serving the Obor district, a major commercial and transport hub in Romania’s capital.
-
B.
Achagua
Achagua are an Indigenous people of the Orinoco region in Colombia and Venezuela, traditionally known for their riverine lifestyle, agriculture, and distinct Arawakan language.
-
C.
Zemst
Zemst is a municipality in the Belgian province of Flemish Brabant, located in the Flanders region.
-
D.
Őrség
Őrség is a scenic, sparsely populated region in western Hungary known for its traditional villages, rolling landscapes, and preserved natural and cultural heritage.
-
E.
Ocuvite
Ocuvite is a line of eye health dietary supplements formulated to support and protect vision, particularly in aging adults.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68852a9a0819097797e31d492e273 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6daedbb4c8190b46846fb1265b937 |
completed | March 27, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c75893a4808190b94a70d8823a01d3 |
completed | March 28, 2026, 4:26 a.m. |
Created at: March 27, 2026, 2:29 p.m.