Triple
T14150486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kacheguda railway station |
E350664
|
entity |
| Predicate | cityStationRank |
P103205
|
FINISHED |
| Object | one of the three major stations in Hyderabad |
—
|
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: one of the three major stations in Hyderabad | Statement: [Kacheguda railway station, cityStationRank, one of the three major stations in Hyderabad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityStationRank Context triple: [Kacheguda railway station, cityStationRank, one of the three major stations in Hyderabad]
-
A.
railwayStationRank
chosen
Indicates the relative importance or classification level assigned to a railway station within a railway network or system.
-
B.
portRank
Indicates the relative importance or hierarchical ranking assigned to a port within a given system or context.
-
C.
areaRank
Indicates the relative ordering or position of an entity based on the size of its area compared to others.
-
D.
capacityRank
Indicates the relative ordering of entities based on how much capacity (e.g., volume, throughput, or capability) they possess compared to others.
-
E.
airportRank
Indicates the relative position or level assigned to an airport within a ranking or ordered list.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6124e23481909e5132a40a1d8624 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:56 a.m.