Triple
T17596034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paniqui, Tarlac, Philippines |
E428574
|
entity |
| Predicate | hasRailwayStation |
P918
|
FINISHED |
| Object |
Paniqui station
Paniqui station is a railway stop serving the municipality of Paniqui in the province of Tarlac in the Philippines.
|
E1467431
|
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: Paniqui station | Statement: [Paniqui, Tarlac, Philippines, hasRailwayStation, Paniqui station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paniqui station Context triple: [Paniqui, Tarlac, Philippines, hasRailwayStation, Paniqui station]
-
A.
Propatria station
Propatria station is a major Caracas Metro station in Venezuela that serves as the western terminus of Line 1.
-
B.
Legarda station
Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
-
C.
Cabitos station
Cabitos station is a stop on Lima Metro’s Line 1 serving passengers in the southern part of Peru’s capital city.
-
D.
Poroy station
Poroy station is a railway station near Cusco, Peru, serving as a key departure point for trains traveling to Machu Picchu and the Sacred Valley.
-
E.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
- 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: Paniqui station Triple: [Paniqui, Tarlac, Philippines, hasRailwayStation, Paniqui station]
Generated description
Paniqui station is a railway stop serving the municipality of Paniqui in the province of Tarlac in the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paniqui station Target entity description: Paniqui station is a railway stop serving the municipality of Paniqui in the province of Tarlac in the Philippines.
-
A.
Propatria station
Propatria station is a major Caracas Metro station in Venezuela that serves as the western terminus of Line 1.
-
B.
Legarda station
Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
-
C.
Cabitos station
Cabitos station is a stop on Lima Metro’s Line 1 serving passengers in the southern part of Peru’s capital city.
-
D.
Poroy station
Poroy station is a railway station near Cusco, Peru, serving as a key departure point for trains traveling to Machu Picchu and the Sacred Valley.
-
E.
Bataizi Station
Bataizi Station is a metro station on Beijing's Batong Line serving passengers in the eastern suburbs of the city.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e469ead59c8190a06519311891af3c |
completed | April 19, 2026, 5:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0965c74be4819092c3bdbc2ac36aff |
completed | May 17, 2026, 6:52 a.m. |
| NEDg | Description generation | batch_6a0966a973c88190a80dea4cac560614 |
completed | May 17, 2026, 6:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09671c01a08190a9034fdb91119c3f |
completed | May 17, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:51 a.m.