Triple
T15365227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comarca de Cuenca de Pamplona |
E367394
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Noáin
Noáin is a municipality in northern Spain’s Navarre region, known for its proximity to Pamplona and its role as a key transport hub with the nearby Pamplona Airport.
|
E1153389
|
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: Noáin | Statement: [Comarca de Cuenca de Pamplona, contains, Noáin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noáin Context triple: [Comarca de Cuenca de Pamplona, contains, Noáin]
-
A.
Noa
Noa is a Hebrew given name commonly used for women in Israel, distinct from the biblical male name Noah.
-
B.
Noe
Noe is a masculine given name used in various cultures, often as a form of Noah.
-
C.
Ojani Noa
Ojani Noa is a Cuban former waiter, model, and actor best known for being Jennifer Lopez’s first husband.
-
D.
Noora
Noora is a feminine given name commonly used in Arabic-speaking and other Muslim-majority cultures, often interpreted to mean "light" or "illumination."
-
E.
Nassim
Nassim is the first name of Nassim Nicholas Taleb, a Lebanese-American scholar, statistician, and former trader known for his work on risk, probability, and uncertainty.
- 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: Noáin Triple: [Comarca de Cuenca de Pamplona, contains, Noáin]
Generated description
Noáin is a municipality in northern Spain’s Navarre region, known for its proximity to Pamplona and its role as a key transport hub with the nearby Pamplona Airport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Noáin Target entity description: Noáin is a municipality in northern Spain’s Navarre region, known for its proximity to Pamplona and its role as a key transport hub with the nearby Pamplona Airport.
-
A.
Noa
Noa is a Hebrew given name commonly used for women in Israel, distinct from the biblical male name Noah.
-
B.
Noe
Noe is a masculine given name used in various cultures, often as a form of Noah.
-
C.
Ojani Noa
Ojani Noa is a Cuban former waiter, model, and actor best known for being Jennifer Lopez’s first husband.
-
D.
Noora
Noora is a feminine given name commonly used in Arabic-speaking and other Muslim-majority cultures, often interpreted to mean "light" or "illumination."
-
E.
Nassim
Nassim is the first name of Nassim Nicholas Taleb, a Lebanese-American scholar, statistician, and former trader known for his work on risk, probability, and uncertainty.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e497de48190be249b110999ec5c |
completed | April 16, 2026, 1:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b4cc39c81908a0aff959352f6d5 |
completed | May 9, 2026, 10:24 a.m. |
| NEDg | Description generation | batch_69ff0df908848190b05c2ecf64f10b08 |
completed | May 9, 2026, 10:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0e8f3b4481909642c91f1a54843c |
completed | May 9, 2026, 10:38 a.m. |
Created at: April 10, 2026, 3:18 a.m.