Triple
T8735795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 9 |
E207378
|
entity |
| Predicate | hasTerminus |
P388
|
FINISHED |
| Object |
Caolu
Caolu is a station in Shanghai, China, serving as the eastern terminus of Shanghai Metro Line 9.
|
E753260
|
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: Caolu | Statement: [Shanghai Metro Line 9, hasTerminus, Caolu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caolu Context triple: [Shanghai Metro Line 9, hasTerminus, Caolu]
-
A.
Kaolie
Kaolie was a monarch of the ancient Chinese state of Chu during the Warring States period, remembered primarily through historical records that preserve his posthumous title.
-
B.
Davo
Davo is a common informal nickname or short form of the given name David, often used in English-speaking countries.
-
C.
Kaala
Kaala is a 2018 Indian Tamil-language action drama film starring Rajinikanth as a slum leader fighting for the rights of oppressed people in Mumbai.
-
D.
Kuo
Kuo is a Wade–Giles romanization of the Chinese surname and name more commonly spelled "Guo" in pinyin.
-
E.
Koloa Talake
Koloa Talake is a Tuvaluan politician who served as the country's prime minister in the early 2000s.
- 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: Caolu Triple: [Shanghai Metro Line 9, hasTerminus, Caolu]
Generated description
Caolu is a station in Shanghai, China, serving as the eastern terminus of Shanghai Metro Line 9.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caolu Target entity description: Caolu is a station in Shanghai, China, serving as the eastern terminus of Shanghai Metro Line 9.
-
A.
Kaolie
Kaolie was a monarch of the ancient Chinese state of Chu during the Warring States period, remembered primarily through historical records that preserve his posthumous title.
-
B.
Davo
Davo is a common informal nickname or short form of the given name David, often used in English-speaking countries.
-
C.
Kaala
Kaala is a 2018 Indian Tamil-language action drama film starring Rajinikanth as a slum leader fighting for the rights of oppressed people in Mumbai.
-
D.
Kuo
Kuo is a Wade–Giles romanization of the Chinese surname and name more commonly spelled "Guo" in pinyin.
-
E.
Koloa Talake
Koloa Talake is a Tuvaluan politician who served as the country's prime minister in the early 2000s.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d44275881909f7eb40b24180294 |
completed | March 31, 2026, 11:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf293a6a3c8190b37738d222b9212f |
completed | April 3, 2026, 2:43 a.m. |
| NEDg | Description generation | batch_69cf2bd4f50c8190bad328e82d299ae0 |
completed | April 3, 2026, 2:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf2cbf60808190a006ee4fb26cde41 |
completed | April 3, 2026, 2:58 a.m. |
Created at: March 30, 2026, 6:37 p.m.