Triple
T17048294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flores |
E413626
|
entity |
| Predicate | connectedTo |
P37
|
FINISHED |
| Object |
San Benito
San Benito is a city in Cameron County, Texas, known for its rich South Texas cultural heritage and proximity to the U.S.–Mexico border.
|
E1247991
|
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: San Benito | Statement: [Flores, connectedTo, San Benito]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Benito Context triple: [Flores, connectedTo, San Benito]
-
A.
San Benito
San Benito is a small coastal town on Siargao Island in the Philippines, known for its laid-back atmosphere, fishing communities, and access to surfing and island-hopping spots.
-
B.
Santa Bárbara
Santa Bárbara is a civil parish within the municipality of Ponta Delgada in the Azores, Portugal.
-
C.
Santa Bárbara
Santa Bárbara is a locality within the Mexican state of Nueva Vizcaya, historically part of New Spain in the colonial era.
-
D.
Santa Bárbara
Santa Bárbara is a small Chilean town in the Biobío Region known for its rural character and proximity to the Biobío River and surrounding forests.
-
E.
Santa Bárbara
Santa Bárbara is a civil parish within the municipality of Vila do Porto in the Azores, Portugal.
- 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: San Benito Triple: [Flores, connectedTo, San Benito]
Generated description
San Benito is a city in Cameron County, Texas, known for its rich South Texas cultural heritage and proximity to the U.S.–Mexico border.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Benito Target entity description: San Benito is a city in Cameron County, Texas, known for its rich South Texas cultural heritage and proximity to the U.S.–Mexico border.
-
A.
San Benito
San Benito is a small coastal town on Siargao Island in the Philippines, known for its laid-back atmosphere, fishing communities, and access to surfing and island-hopping spots.
-
B.
Santa Bárbara
Santa Bárbara is a locality within the Mexican state of Nueva Vizcaya, historically part of New Spain in the colonial era.
-
C.
Santa Bárbara
Santa Bárbara is a small Chilean town in the Biobío Region known for its rural character and proximity to the Biobío River and surrounding forests.
-
D.
Santa Bárbara
Santa Bárbara is a civil parish within the municipality of Ponta Delgada in the Azores, Portugal.
-
E.
Santa Bárbara
Santa Bárbara is a civil parish within the municipality of Vila do Porto in the Azores, Portugal.
- 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_69d886cd18288190b006abab23f811b7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3da9f799c8190a683ae38cd990643 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01233fb8d88190a9a6ef6a2f19a499 |
completed | May 11, 2026, 12:30 a.m. |
| NEDg | Description generation | batch_6a012533f9a8819096ab9b821c848dd2 |
completed | May 11, 2026, 12:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0125dead2481908a5c26bda5a7cd1f |
completed | May 11, 2026, 12:42 a.m. |
Created at: April 10, 2026, 5:34 a.m.