Triple
T1615114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamaulipas |
E34698
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Tampico |
E81128
|
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: Tampico | Statement: [Tamaulipas, containsCity, Tampico]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tampico Context triple: [Tamaulipas, containsCity, Tampico]
-
A.
Tampico, Mexico
chosen
Tampico, Mexico is a major port city on the Gulf of Mexico in the state of Tamaulipas, known historically for its oil industry and commercial significance.
-
B.
Port of Veracruz
The Port of Veracruz is one of Mexico’s oldest and most important seaports, serving as a key hub for international trade on the Gulf of Mexico.
-
C.
Matamoros
Matamoros is a Mexican border city in the state of Tamaulipas, located directly across the Rio Grande from Brownsville, Texas, and known as an important hub for trade and manufacturing.
-
D.
Manzanillo
Manzanillo is a major Pacific coastal city in western Mexico known for its busy commercial port and popular beach tourism.
-
E.
Mazatlán, Mexico
Mazatlán, Mexico is a Pacific coastal city in the state of Sinaloa known for its long sandy beaches, historic old town, and major seaport and tourism industry.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a9098f384c81909ef836ee779466e2 |
completed | March 5, 2026, 4:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad51ca2bc48190abb83f4d84782334 |
completed | March 8, 2026, 10:39 a.m. |
Created at: March 4, 2026, 7:28 p.m.