Triple
T3376562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyderabad Metro |
E71079
|
entity |
| Predicate | peakDirectionCapacity |
P14460
|
FINISHED |
| Object | high passenger throughput |
—
|
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: high passenger throughput | Statement: [Hyderabad Metro, peakDirectionCapacity, high passenger throughput]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakDirectionCapacity Context triple: [Hyderabad Metro, peakDirectionCapacity, high passenger throughput]
-
A.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
B.
maximumCapacity
chosen
Indicates the greatest allowable or designed amount of something that an entity can hold, contain, or handle.
-
C.
peakUse
Indicates the time, condition, or context in which something reaches its maximum level of use or intensity.
-
D.
peakStatus
Indicates the condition or phase of something at its highest or most intense point in its progression or lifecycle.
-
E.
peakType
Indicates the specific classification or category of a peak based on its form, prominence, or other defining characteristics.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2e776508190bc123fb17b36f062 |
completed | March 8, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69ada433059881908e46f38cc5f40a32 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.