Triple
T3758673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tunis Metro |
E82109
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 4
Line 4 is a route of the Tunis Metro light rail network serving parts of the Tunis metropolitan area in Tunisia.
|
E390791
|
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 4 | Statement: [Tunis Metro, hasLine, Line 4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 4 Context triple: [Tunis Metro, hasLine, Line 4]
-
A.
Line 4
Line 4 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
-
B.
Line 4
Line 4 is a major line of the Santiago Metro in Chile, serving key residential and commercial areas in the southeastern part of the city.
-
C.
Line 4
Line 4 is a major north–south rapid transit route in the Beijing Subway system, serving key commercial, residential, and university areas of the city.
-
D.
Line 4
Line 4 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving key urban and suburban areas along its north–south corridor.
-
E.
Line 4
Line 4 is one of the main lines of the Tehran Metro rapid transit system, serving key east–west corridors across Iran’s capital 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: Line 4 Triple: [Tunis Metro, hasLine, Line 4]
Generated description
Line 4 is a route of the Tunis Metro light rail network serving parts of the Tunis metropolitan area in Tunisia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 4 Target entity description: Line 4 is a route of the Tunis Metro light rail network serving parts of the Tunis metropolitan area in Tunisia.
-
A.
Line 4
Line 4 is a rapid transit line of the Barcelona Metro network that serves several central and coastal neighborhoods in the city.
-
B.
Line 4
Line 4 is one of the main north–south lines of the Paris Métro, known for serving central Paris and connecting key railway stations and neighborhoods.
-
C.
Line 4
Line 4 is a planned rapid transit route within the future Ho Chi Minh City Metro system in Vietnam.
-
D.
Line 4
Line 4 is a circular rapid transit route of the Shanghai Metro system that loops around central districts and provides key transfer connections across the network.
-
E.
Line 4
Line 4 is a major line of the Santiago Metro in Chile, serving key residential and commercial areas in the southeastern part 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcbc20b20819095fedf803aadc53a |
completed | March 8, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fb0fc6248190b2f4adf3fd2d73d9 |
completed | March 14, 2026, 6:07 a.m. |
| NEDg | Description generation | batch_69b4fc9107fc81908805740b98c7ae3e |
completed | March 14, 2026, 6:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4fced2620819083ab1e75393ba2ba |
completed | March 14, 2026, 6:15 a.m. |
Created at: March 8, 2026, 3:35 p.m.