Triple
T4754002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferozepur |
E105542
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
PB-05
PB-05 is the regional vehicle registration code assigned to the Ferozepur district in the Indian state of Punjab.
|
E467563
|
NE FINISHED |
How this triple was built (4 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: PB-05 | Statement: [Ferozepur, vehicleRegistrationCode, PB-05]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PB-05 Context triple: [Ferozepur, vehicleRegistrationCode, PB-05]
-
A.
PB-02
PB-02 is the regional vehicle registration code assigned to the Amritsar district in the Indian state of Punjab.
-
B.
P54C
P54C is the second-generation Intel Pentium microprocessor core, notable for introducing a refined 0.35 μm design and improved performance over the original Pentium (P5).
-
C.
P5
P5 is the CERN Large Hadron Collider interaction point that hosts the CMS experiment and associated infrastructure.
-
D.
P5
P5 is a common abbreviation for the “Power Five,” the group of the five most prominent NCAA Division I college athletic conferences in the United States.
-
E.
PBXN-109
PBXN-109 is a modern, insensitive high-explosive formulation used in military munitions to provide high blast performance with improved safety against accidental detonation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: PB-05 Triple: [Ferozepur, vehicleRegistrationCode, PB-05]
Generated description
PB-05 is the regional vehicle registration code assigned to the Ferozepur district in the Indian state of Punjab.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PB-05 Target entity description: PB-05 is the regional vehicle registration code assigned to the Ferozepur district in the Indian state of Punjab.
-
A.
PB-02
PB-02 is the regional vehicle registration code assigned to the Amritsar district in the Indian state of Punjab.
-
B.
P54C
P54C is the second-generation Intel Pentium microprocessor core, notable for introducing a refined 0.35 μm design and improved performance over the original Pentium (P5).
-
C.
P5
P5 is the CERN Large Hadron Collider interaction point that hosts the CMS experiment and associated infrastructure.
-
D.
P5
P5 is a common abbreviation for the “Power Five,” the group of the five most prominent NCAA Division I college athletic conferences in the United States.
-
E.
PBXN-109
PBXN-109 is a modern, insensitive high-explosive formulation used in military munitions to provide high blast performance with improved safety against accidental detonation.
- F. None of above. chosen
Provenance (5 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64e72d1c81908eb60960751e52b1 |
completed | March 20, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be3a6600e481909c3fb1decf23d7d8 |
completed | March 21, 2026, 6:27 a.m. |
| NEDg | Description generation | batch_69be3d05e8a081908cdcb37620078fa6 |
completed | March 21, 2026, 6:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be3daa7e0081908971df65613c9df6 |
completed | March 21, 2026, 6:41 a.m. |
Created at: March 20, 2026, 1:20 p.m.