Triple
T1658608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tehran Metro |
E35854
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 6
Line 6 is a major north–south route of the Tehran Metro system, serving numerous key districts across Iran’s capital city.
|
E187609
|
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: Line 6 | Statement: [Tehran Metro, hasLine, Line 6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 6 Context triple: [Tehran Metro, hasLine, Line 6]
-
A.
Line 6
Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
-
B.
Line 6
Line 6 is a route of Mexico City’s Metrobús bus rapid transit system that serves as one of the network’s main corridors.
-
C.
Line 6
Line 6 is a modern, fully automated metro line in the Santiago Metro system in Chile, known for its driverless trains and advanced safety features.
-
D.
Line 6
Line 6 is a major rapid transit route in the Beijing Subway system that runs east–west across the city, helping to relieve congestion on other central lines.
-
E.
Line 6
Line 6 is a route of the Mexico City Metro system that runs east–west across the northern part of the city, connecting several residential and commercial areas.
- 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: Line 6 Triple: [Tehran Metro, hasLine, Line 6]
Generated description
Line 6 is a major north–south route of the Tehran Metro system, serving numerous key districts across Iran’s capital city.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 6 Target entity description: Line 6 is a major north–south route of the Tehran Metro system, serving numerous key districts across Iran’s capital city.
-
A.
Line 6
Line 6 is a route of Mexico City’s Metrobús bus rapid transit system that serves as one of the network’s main corridors.
-
B.
Line 6
Line 6 is a modern, fully automated metro line in the Santiago Metro system in Chile, known for its driverless trains and advanced safety features.
-
C.
Line 6
Line 6 is a major rapid transit route in the Beijing Subway system that runs east–west across the city, helping to relieve congestion on other central lines.
-
D.
Line 6
Line 6 is a route of the Mexico City Metro system that runs east–west across the northern part of the city, connecting several residential and commercial areas.
-
E.
Line 6
Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
- 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_69a88606aa808190aa0b421b4271f220 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90aafe5e881908158fab83998fd07 |
completed | March 5, 2026, 4:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad6827ff2c8190b7c9af9926a7452c |
completed | March 8, 2026, 12:14 p.m. |
| NEDg | Description generation | batch_69ad68edbd2c819090c6556966eb279a |
completed | March 8, 2026, 12:17 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad69724c9c8190a2314a8f30f18f7d |
completed | March 8, 2026, 12:20 p.m. |
Created at: March 4, 2026, 7:29 p.m.