Triple
T25128666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universitate |
E629462
|
entity |
| Predicate | followedByStationOnLineM2 |
P162987
|
FINISHED |
| Object | Piața Unirii |
—
|
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: Piața Unirii | Statement: [Universitate, followedByStationOnLineM2, Piața Unirii]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: followedByStationOnLineM2 Context triple: [Universitate, followedByStationOnLineM2, Piața Unirii]
-
A.
followedByStationOnLine1
Indicates that one station directly succeeds another station along the sequence of stops on Line 1.
-
B.
followedByStation
Indicates that one station directly succeeds another in a sequence, such as along a transit line or route.
-
C.
hasAdjacentStationOnLine 5
Indicates that one station is directly next to another station along line 5, with no other stations in between on that line.
-
D.
hasAdjacentStationOnLine 2
Indicates that one station is directly next to another station along Line 2 in the network.
-
E.
adjacentStationOnLineD
Indicates that one station is directly next to another station along line D, with no other stations in between on that line.
- 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_69e2ff3288048190bd82c3b7f7bd0e62 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f63639a84c81909d700a539b458b42 |
completed | May 2, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69f63182f1408190bddc1214fcbd6145 |
completed | May 2, 2026, 5:16 p.m. |
| PDg | Predicate description generation | batch_69f6352df6148190bc10772cd40bd7b3 |
completed | May 2, 2026, 5:32 p.m. |
Created at: April 18, 2026, 6:28 a.m.