Triple
T14988519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraćin |
E373768
|
entity |
| Predicate | vehicleRegistrationCode |
P1173
|
FINISHED |
| Object |
PN
PN is the vehicle registration code used on license plates for the town of Paraćin in Serbia.
|
E1129545
|
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: PN | Statement: [Paraćin, vehicleRegistrationCode, PN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PN Context triple: [Paraćin, vehicleRegistrationCode, PN]
-
A.
PN
PN is the official abbreviation for the Philippine Navy, the naval warfare branch of the Armed Forces of the Philippines.
-
B.
PN
PN is the vehicle registration code used for the Italian city and province of Pordenone in the Friuli Venezia Giulia region.
-
C.
PN
PN is the commonly used abbreviation for the National Parliament of East Timor, the country's unicameral legislative body.
-
D.
PN
PN is the station code for Penn–North station on the Baltimore Metro SubwayLink system.
-
E.
PNP
The PNP is the national law enforcement agency of Peru responsible for maintaining public order, preventing and investigating crime, and ensuring internal security across the country.
- 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: PN Triple: [Paraćin, vehicleRegistrationCode, PN]
Generated description
PN is the vehicle registration code used on license plates for the town of Paraćin in Serbia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PN Target entity description: PN is the vehicle registration code used on license plates for the town of Paraćin in Serbia.
-
A.
PN
PN is the official abbreviation for the Philippine Navy, the naval warfare branch of the Armed Forces of the Philippines.
-
B.
PN
PN is the vehicle registration code used for the Italian city and province of Pordenone in the Friuli Venezia Giulia region.
-
C.
PN
PN is the commonly used abbreviation for the National Parliament of East Timor, the country's unicameral legislative body.
-
D.
PN
PN is the station code for Penn–North station on the Baltimore Metro SubwayLink system.
-
E.
PNP
The PNP is the national law enforcement agency of Peru responsible for maintaining public order, preventing and investigating crime, and ensuring internal security across the country.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7148a308190a687f4d0d61397c6 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8c036bfc8190b01bf2128403f557 |
completed | May 9, 2026, 1:21 a.m. |
| NEDg | Description generation | batch_69fe8dc977448190a01c55d99d4d9034 |
completed | May 9, 2026, 1:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe8e9e62a4819089b3568d277d5262 |
completed | May 9, 2026, 1:32 a.m. |
Created at: April 10, 2026, 2:53 a.m.