Triple
T10134548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Padre Island National Seashore |
E226822
|
entity |
| Predicate | hasWaterBody |
P165
|
FINISHED |
| Object | Laguna Madre |
E775883
|
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: Laguna Madre | Statement: [Padre Island National Seashore, hasWaterBody, Laguna Madre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laguna Madre Context triple: [Padre Island National Seashore, hasWaterBody, Laguna Madre]
-
A.
Laguna Madre
chosen
Laguna Madre is a long, shallow hypersaline lagoon along the Texas Gulf Coast known for its rich biodiversity and importance as a habitat for migratory birds and marine life.
-
B.
Laguna Atascosa
Laguna Atascosa is a shallow coastal lagoon in southern Texas that forms part of an important wetland and wildlife habitat along the Gulf Coast.
-
C.
Bahía Maguey
Bahía Maguey is a scenic beach bay in the Huatulco region of Oaxaca, Mexico, known for its calm waters, seafood restaurants, and boat tours.
-
D.
Laguna
Laguna is a province in the Philippines known for its hot springs, lakeside towns around Laguna de Bay, and as the birthplace of national hero José Rizal.
-
E.
Laguna
Laguna is the internal codename Apple used for its early Macintosh Portable computer model.
- 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_69ca8433ec308190b8b25a6fe359c34c |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cde87e1f908190a53865420f2b8f93 |
completed | April 2, 2026, 3:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2e5d98a148190ada7082adb98ddaa |
completed | April 5, 2026, 10:44 p.m. |
Created at: March 30, 2026, 9:06 p.m.