Triple
T3203630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Port Harcourt |
E67106
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
UNIPORT
UNIPORT is a Nigerian federal university located in Port Harcourt, renowned for its programs in petroleum engineering and other science and humanities disciplines.
|
E335152
|
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: UNIPORT | Statement: [University of Port Harcourt, shortName, UNIPORT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: UNIPORT Context triple: [University of Port Harcourt, shortName, UNIPORT]
-
A.
UIO
UIO is the IATA airport code for Mariscal Sucre International Airport serving Quito, Ecuador.
-
B.
IPU
IPU is the commonly used abbreviation for the Inter-Parliamentary Union, a global organization that fosters cooperation and dialogue among national parliaments.
-
C.
Iputinga
Iputinga is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
-
D.
UNBISnet
UNBISnet is the United Nations Bibliographic Information System, an online catalog and database providing access to UN documents and publications.
-
E.
UCA
UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
- 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: UNIPORT Triple: [University of Port Harcourt, shortName, UNIPORT]
Generated description
UNIPORT is a Nigerian federal university located in Port Harcourt, renowned for its programs in petroleum engineering and other science and humanities disciplines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: UNIPORT Target entity description: UNIPORT is a Nigerian federal university located in Port Harcourt, renowned for its programs in petroleum engineering and other science and humanities disciplines.
-
A.
UIO
UIO is the IATA airport code for Mariscal Sucre International Airport serving Quito, Ecuador.
-
B.
IPU
IPU is the commonly used abbreviation for the Inter-Parliamentary Union, a global organization that fosters cooperation and dialogue among national parliaments.
-
C.
Iputinga
Iputinga is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
-
D.
UNBISnet
UNBISnet is the United Nations Bibliographic Information System, an online catalog and database providing access to UN documents and publications.
-
E.
UCA
UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9b188a88190b7b5e9b3be9410db |
completed | March 8, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b24bcbb0e88190b4413c4ba3de0eeb |
completed | March 12, 2026, 5:14 a.m. |
| NEDg | Description generation | batch_69b24ca05434819080ee515b1e7bdcb4 |
completed | March 12, 2026, 5:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b24d19250c81908a9c3ac95b83a473 |
completed | March 12, 2026, 5:20 a.m. |
Created at: March 8, 2026, 3:07 p.m.