Triple
T1256371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UNP |
E12401
|
entity |
| Predicate | tradedAs |
P2822
|
FINISHED |
| Object | UNP |
E12401
|
NE 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: UNP | Statement: [UNP, tradedAs, UNP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UNP Context triple: [UNP, tradedAs, UNP]
-
A.
UNP
chosen
UNP is the stock ticker symbol for Union Pacific Corporation, one of the largest freight railroad companies in the United States.
-
B.
UNOV
UNOV is one of the main United Nations headquarters, located in Vienna, Austria, hosting various UN offices and agencies focused on issues such as drugs and crime, outer space affairs, and industrial development.
-
C.
NU
NU is the official two-letter Canada Post abbreviation for the northern Canadian territory of Nunavut.
-
D.
NU
NU is a leading Japanese national research university located in Nagoya, known for its strong programs in science, engineering, and the humanities.
-
E.
UNON
UNON is the United Nations Office at Nairobi, a major UN headquarters in Africa that hosts and supports numerous UN agencies and programs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfa726548190911b4022dc1be3c3 |
completed | March 1, 2026, 10:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac93cb76248190a23acb2e76ecfa8d |
completed | March 7, 2026, 9:08 p.m. |
Created at: March 1, 2026, 7:50 p.m.