Triple
T4058657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarlac |
E84755
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Tarlac City |
E84755
|
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: Tarlac City | Statement: [Tarlac, capital, Tarlac City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarlac City Context triple: [Tarlac, capital, Tarlac City]
-
A.
Tarlac
chosen
Tarlac is a landlocked province in the Central Luzon region of the Philippines known for its culturally diverse population and agricultural economy.
-
B.
Laoag
Laoag is a coastal city in northern Luzon, Philippines, known as the capital of Ilocos Norte and a regional center for commerce, education, and tourism.
-
C.
Mabalacat
Mabalacat is a city in the Philippine province of Pampanga known for hosting part of Clark Freeport and Special Economic Zone, a major commercial and aviation hub.
-
D.
Meycauayan
Meycauayan is a highly urbanized city in the Philippine province of Bulacan known for its jewelry and leather industries.
-
E.
Tuguegarao City
Tuguegarao City is a major urban and commercial center in northeastern Luzon in the Philippines, known for its hot climate and role as a regional hub for education, trade, and government services.
- 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_69aed933bec881909edfa28ebb69c634 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefbd13b4481908f9c09cc4f4a9724 |
completed | March 9, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be10079a408190ae09d3df55ead73c |
completed | March 21, 2026, 3:27 a.m. |
Created at: March 9, 2026, 3:38 p.m.